commit 721b00bbb65ccf75b83780b48abcf49ad1f10181
parent f5555b89ba4cff61c189f54b321393ff4a414842
Author: Andrew <andrewlaack1@gmail.com>
Date: Thu, 24 Oct 2024 20:57:50 -0500
finished some stuff
Diffstat:
3 files changed, 674 insertions(+), 282 deletions(-)
diff --git a/.gitignore b/.gitignore
@@ -1,5 +1,4 @@
datasets/
models/
graphs/
-aiImageDetection/OriginalImages
-aiImageDetection/ManipulatedImages-
\ No newline at end of file
+trickAIImageDetection/img+
\ No newline at end of file
diff --git a/nnPruning/NaivePruningFashion.ipynb b/nnPruning/NaivePruningFashion.ipynb
@@ -22,7 +22,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -31,7 +31,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -41,7 +41,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
@@ -54,7 +54,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
@@ -76,20 +76,20 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
- "2024-10-24 17:48:44.695240: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
- "2024-10-24 17:48:44.698161: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
- "2024-10-24 17:48:44.731310: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+ "2024-10-24 18:24:43.772336: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
+ "2024-10-24 18:24:43.775524: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
+ "2024-10-24 18:24:43.810055: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
"To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
- "2024-10-24 17:48:45.486756: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
- "2024-10-24 17:48:46.001707: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
- "2024-10-24 17:48:46.002168: W tensorflow/core/common_runtime/gpu/gpu_device.cc:2251] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.\n",
+ "2024-10-24 18:24:44.679315: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+ "2024-10-24 18:24:45.248637: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355\n",
+ "2024-10-24 18:24:45.249161: W tensorflow/core/common_runtime/gpu/gpu_device.cc:2251] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.\n",
"Skipping registering GPU devices...\n"
]
},
@@ -220,7 +220,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
@@ -229,7 +229,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 7,
"metadata": {},
"outputs": [
{
@@ -237,114 +237,114 @@
"output_type": "stream",
"text": [
"Epoch 1/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 22ms/step - accuracy: 0.7331 - loss: 0.8068\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 32ms/step - accuracy: 0.7375 - loss: 0.7716\n",
"Epoch 2/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 24ms/step - accuracy: 0.8655 - loss: 0.3676\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 33ms/step - accuracy: 0.8678 - loss: 0.3647\n",
"Epoch 3/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 22ms/step - accuracy: 0.8797 - loss: 0.3269\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 39ms/step - accuracy: 0.8786 - loss: 0.3285\n",
"Epoch 4/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 24ms/step - accuracy: 0.8842 - loss: 0.3114\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 35ms/step - accuracy: 0.8861 - loss: 0.3101\n",
"Epoch 5/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 21ms/step - accuracy: 0.8952 - loss: 0.2835\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 32ms/step - accuracy: 0.8943 - loss: 0.2837\n",
"Epoch 6/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 22ms/step - accuracy: 0.9004 - loss: 0.2667\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 32ms/step - accuracy: 0.9000 - loss: 0.2692\n",
"Epoch 7/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 28ms/step - accuracy: 0.9062 - loss: 0.2503\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 30ms/step - accuracy: 0.8991 - loss: 0.2695\n",
"Epoch 8/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9103 - loss: 0.2427\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 30ms/step - accuracy: 0.9078 - loss: 0.2503\n",
"Epoch 9/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 21ms/step - accuracy: 0.9138 - loss: 0.2289\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 30ms/step - accuracy: 0.9122 - loss: 0.2362\n",
"Epoch 10/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 26ms/step - accuracy: 0.9205 - loss: 0.2146\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 30ms/step - accuracy: 0.9103 - loss: 0.2389\n",
"Epoch 11/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 26ms/step - accuracy: 0.9213 - loss: 0.2116\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9156 - loss: 0.2276\n",
"Epoch 12/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 29ms/step - accuracy: 0.9259 - loss: 0.1997\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 29ms/step - accuracy: 0.9210 - loss: 0.2074\n",
"Epoch 13/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 27ms/step - accuracy: 0.9240 - loss: 0.2029\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 29ms/step - accuracy: 0.9208 - loss: 0.2077\n",
"Epoch 14/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 27ms/step - accuracy: 0.9281 - loss: 0.1909\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 29ms/step - accuracy: 0.9154 - loss: 0.2279\n",
"Epoch 15/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 23ms/step - accuracy: 0.9295 - loss: 0.1853\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9199 - loss: 0.2131\n",
"Epoch 16/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9305 - loss: 0.1852\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 29ms/step - accuracy: 0.9235 - loss: 0.2022\n",
"Epoch 17/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 28ms/step - accuracy: 0.9330 - loss: 0.1741\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 28ms/step - accuracy: 0.9288 - loss: 0.1867\n",
"Epoch 18/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 23ms/step - accuracy: 0.9381 - loss: 0.1650\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 40ms/step - accuracy: 0.9326 - loss: 0.1776\n",
"Epoch 19/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9388 - loss: 0.1623\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 37ms/step - accuracy: 0.9376 - loss: 0.1660\n",
"Epoch 20/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 25ms/step - accuracy: 0.9430 - loss: 0.1504\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 41ms/step - accuracy: 0.9390 - loss: 0.1627\n",
"Epoch 21/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 22ms/step - accuracy: 0.9436 - loss: 0.1471\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 32ms/step - accuracy: 0.9390 - loss: 0.1630\n",
"Epoch 22/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 24ms/step - accuracy: 0.9465 - loss: 0.1428\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 31ms/step - accuracy: 0.9427 - loss: 0.1523\n",
"Epoch 23/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9458 - loss: 0.1471\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 30ms/step - accuracy: 0.9428 - loss: 0.1503\n",
"Epoch 24/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9464 - loss: 0.1415\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 36ms/step - accuracy: 0.9437 - loss: 0.1491\n",
"Epoch 25/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 24ms/step - accuracy: 0.9503 - loss: 0.1316\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 40ms/step - accuracy: 0.9437 - loss: 0.1465\n",
"Epoch 26/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 24ms/step - accuracy: 0.9499 - loss: 0.1338\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 39ms/step - accuracy: 0.9443 - loss: 0.1460\n",
"Epoch 27/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9521 - loss: 0.1266\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 38ms/step - accuracy: 0.9524 - loss: 0.1270\n",
"Epoch 28/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 26ms/step - accuracy: 0.9503 - loss: 0.1312\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9511 - loss: 0.1301\n",
"Epoch 29/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9491 - loss: 0.1332\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 30ms/step - accuracy: 0.9518 - loss: 0.1258\n",
"Epoch 30/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 25ms/step - accuracy: 0.9559 - loss: 0.1167\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 32ms/step - accuracy: 0.9560 - loss: 0.1176\n",
"Epoch 31/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 25ms/step - accuracy: 0.9591 - loss: 0.1071\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 30ms/step - accuracy: 0.9563 - loss: 0.1128\n",
"Epoch 32/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9596 - loss: 0.1069\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 39ms/step - accuracy: 0.9584 - loss: 0.1101\n",
"Epoch 33/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 29ms/step - accuracy: 0.9621 - loss: 0.1010\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 48ms/step - accuracy: 0.9565 - loss: 0.1139\n",
"Epoch 34/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 25ms/step - accuracy: 0.9586 - loss: 0.1062\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 28ms/step - accuracy: 0.9609 - loss: 0.1047\n",
"Epoch 35/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 26ms/step - accuracy: 0.9635 - loss: 0.0967\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9482 - loss: 0.1363\n",
"Epoch 36/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 26ms/step - accuracy: 0.9640 - loss: 0.0968\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 28ms/step - accuracy: 0.9530 - loss: 0.1272\n",
"Epoch 37/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 25ms/step - accuracy: 0.9654 - loss: 0.0919\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 34ms/step - accuracy: 0.9604 - loss: 0.1092\n",
"Epoch 38/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9672 - loss: 0.0857\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 37ms/step - accuracy: 0.9615 - loss: 0.1040\n",
"Epoch 39/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 27ms/step - accuracy: 0.9659 - loss: 0.0893\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 36ms/step - accuracy: 0.9667 - loss: 0.0922\n",
"Epoch 40/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 25ms/step - accuracy: 0.9696 - loss: 0.0817\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 35ms/step - accuracy: 0.9655 - loss: 0.0915\n",
"Epoch 41/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 25ms/step - accuracy: 0.9701 - loss: 0.0784\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 44ms/step - accuracy: 0.9677 - loss: 0.0860\n",
"Epoch 42/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 24ms/step - accuracy: 0.9718 - loss: 0.0729\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 33ms/step - accuracy: 0.9702 - loss: 0.0811\n",
"Epoch 43/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 26ms/step - accuracy: 0.9700 - loss: 0.0807\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 33ms/step - accuracy: 0.9701 - loss: 0.0793\n",
"Epoch 44/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 25ms/step - accuracy: 0.9666 - loss: 0.0858\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 32ms/step - accuracy: 0.9668 - loss: 0.0857\n",
"Epoch 45/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9646 - loss: 0.0909\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 35ms/step - accuracy: 0.9705 - loss: 0.0770\n",
"Epoch 46/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9717 - loss: 0.0757\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 34ms/step - accuracy: 0.9741 - loss: 0.0701\n",
"Epoch 47/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 25ms/step - accuracy: 0.9751 - loss: 0.0662\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 33ms/step - accuracy: 0.9734 - loss: 0.0705\n",
"Epoch 48/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 24ms/step - accuracy: 0.9738 - loss: 0.0668\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 35ms/step - accuracy: 0.9708 - loss: 0.0734\n",
"Epoch 49/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 25ms/step - accuracy: 0.9756 - loss: 0.0646\n",
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 33ms/step - accuracy: 0.9751 - loss: 0.0649\n",
"Epoch 50/50\n",
- "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 25ms/step - accuracy: 0.9741 - loss: 0.0664\n"
+ "\u001b[1m60/60\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 34ms/step - accuracy: 0.9732 - loss: 0.0715\n"
]
},
{
"data": {
"text/plain": [
- "<keras.src.callbacks.history.History at 0x7f5852af0bd0>"
+ "<keras.src.callbacks.history.History at 0x7f2181911690>"
]
},
- "execution_count": 8,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
@@ -355,14 +355,14 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 1ms/step\n"
+ "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step\n"
]
}
],
@@ -372,18 +372,18 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "array([9.9220973e-01, 5.9291801e-07, 1.4035820e-06, 3.1673932e-07,\n",
- " 4.2094553e-06, 1.4789060e-09, 7.7837552e-03, 2.4453586e-10,\n",
- " 3.8267243e-09, 7.6906943e-09], dtype=float32)"
+ "array([9.9677068e-01, 4.0155374e-08, 7.2944522e-06, 4.5611072e-05,\n",
+ " 2.9083214e-05, 1.5283574e-06, 2.8001778e-03, 2.7095768e-07,\n",
+ " 3.4529122e-04, 3.2940815e-08], dtype=float32)"
]
},
- "execution_count": 10,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -394,7 +394,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
@@ -403,7 +403,7 @@
"array([1., 0., 0., 0., 0., 0., 0., 0., 0., 0.])"
]
},
- "execution_count": 11,
+ "execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
@@ -414,7 +414,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
@@ -426,7 +426,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
@@ -437,16 +437,16 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[0, 1, 2, 2, 3, 6, 8, 6, 5, 0]"
+ "[0, 1, 2, 2, 3, 6, 8, 2, 5, 0]"
]
},
- "execution_count": 14,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -457,7 +457,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 14,
"metadata": {},
"outputs": [
{
@@ -466,7 +466,7 @@
"[0, 1, 2, 2, 3, 2, 8, 6, 5, 0]"
]
},
- "execution_count": 15,
+ "execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
@@ -477,16 +477,16 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "0.8995"
+ "0.8982"
]
},
- "execution_count": 16,
+ "execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
@@ -499,23 +499,23 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[[840 1 14 12 3 4 119 1 6 0]\n",
- " [ 2 986 1 8 0 0 3 0 0 0]\n",
- " [ 13 0 816 8 120 0 38 0 5 0]\n",
- " [ 17 22 7 898 31 1 23 0 1 0]\n",
- " [ 2 2 39 18 901 1 36 0 1 0]\n",
- " [ 0 0 0 0 0 952 0 31 5 12]\n",
- " [101 2 78 22 81 0 712 0 4 0]\n",
- " [ 0 0 0 0 0 6 0 976 1 17]\n",
- " [ 4 0 4 1 4 2 10 2 972 1]\n",
- " [ 0 0 0 0 0 3 0 54 1 942]]\n"
+ "[[890 0 15 13 0 2 72 0 8 0]\n",
+ " [ 1 992 1 4 0 1 1 0 0 0]\n",
+ " [ 21 0 860 12 47 2 53 0 5 0]\n",
+ " [ 32 13 8 908 22 1 14 0 2 0]\n",
+ " [ 2 2 120 21 810 0 42 1 2 0]\n",
+ " [ 0 0 0 0 0 958 1 28 3 10]\n",
+ " [168 1 76 28 53 0 664 0 10 0]\n",
+ " [ 0 0 0 0 0 9 0 970 0 21]\n",
+ " [ 2 0 3 3 2 3 7 1 978 1]\n",
+ " [ 0 0 0 0 0 5 0 43 0 952]]\n"
]
}
],
@@ -528,12 +528,12 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
@@ -557,178 +557,162 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "* 0 T-shirt/top\n",
- "* 1 Trouser\n",
- "* 2 Pullover\n",
- "* 3 Dress\n",
- "* 4 Coat\n",
- "* 5 Sandal\n",
- "* 6 Shirt\n",
- "* 7 Sneaker\n",
- "* 8 Bag\n",
- "* 9 Ankle boot"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
"1408 neurons * .024 percent ~= 34 neurons"
]
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[array([[ 0.08454783, -0.05098309, -0.04616751, ..., 0.06632042,\n",
- " -0.05217841, 0.01232629],\n",
- " [-0.0529512 , 0.00467757, -0.03662501, ..., -0.08718916,\n",
- " 0.01971413, 0.05872909],\n",
- " [ 0.03779383, -0.04091078, 0.02633846, ..., -0.00778965,\n",
- " -0.05630131, 0.04108118],\n",
+ "[array([[-0.02407834, 0.01664758, 0.05549181, ..., 0.0705011 ,\n",
+ " 0.03139306, 0.0338089 ],\n",
+ " [-0.01324078, -0.08908298, 0.02861458, ..., 0.02894005,\n",
+ " -0.0171534 , -0.06429082],\n",
+ " [-0.03732396, -0.08407578, -0.05166027, ..., 0.04460023,\n",
+ " 0.03189332, 0.02576386],\n",
" ...,\n",
- " [ 0.01152897, -0.08101085, 0.01823257, ..., -0.0205617 ,\n",
- " -0.12606516, -0.04726963],\n",
- " [ 0.02434475, -0.05446399, 0.00161054, ..., 0.0015396 ,\n",
- " -0.01188318, -0.10043874],\n",
- " [-0.04427422, -0.00988704, 0.04262575, ..., -0.02058123,\n",
- " -0.05206178, 0.00558643]], dtype=float32),\n",
- " array([ 6.67025149e-02, -6.48351908e-02, 8.96135904e-03, 7.74898753e-02,\n",
- " 5.02208099e-02, 5.26248105e-03, -8.10043048e-03, -1.04107223e-02,\n",
- " 5.62812723e-02, -4.39162273e-03, 2.36019883e-02, -3.15822624e-02,\n",
- " -1.03224767e-03, -3.70393880e-02, 8.60195793e-03, -8.09552893e-03,\n",
- " 3.91760319e-02, 6.49746358e-02, 3.39787191e-04, 3.13962139e-02,\n",
- " -1.64847877e-02, 3.46672311e-02, 1.32310912e-01, -5.89670334e-03,\n",
- " -1.33697288e-02, 2.63240635e-02, 4.48439550e-03, 4.54737898e-03,\n",
- " 2.62818299e-02, 1.96660496e-02, 2.91804709e-02, 3.23776193e-02,\n",
- " 1.00882715e-02, 2.12802663e-02, -2.16822717e-02, 4.86880951e-02,\n",
- " 1.27961803e-02, -6.23180307e-02, -6.86503015e-03, 2.19246242e-02,\n",
- " -3.80160213e-02, -1.33764772e-02, -2.78035309e-02, 7.24991113e-02,\n",
- " 4.38980833e-02, -1.31145567e-02, -7.95331821e-02, 1.17829353e-01,\n",
- " 7.65682906e-02, 9.42144636e-03, -3.09614856e-02, -2.08251737e-02,\n",
- " 1.82664096e-02, 7.76899457e-02, 1.83460470e-02, 2.59148236e-02,\n",
- " 4.43009287e-03, 3.60324117e-03, 1.61220366e-03, 8.12385678e-02,\n",
- " 1.42841628e-02, -2.38703247e-02, 4.01736461e-02, 2.70666610e-02,\n",
- " 8.19975436e-02, -1.48505475e-02, -2.33125910e-02, 1.11394949e-01,\n",
- " 1.42461740e-05, -5.39243370e-02, 8.54932517e-02, 2.44116765e-02,\n",
- " -2.71408446e-02, 1.70381535e-02, 1.36350328e-02, -2.29779389e-02,\n",
- " 2.54731299e-03, 1.58162937e-02, 5.09508699e-03, -5.74031845e-02,\n",
- " -1.41982650e-02, -6.57597110e-02, 3.00787967e-02, -2.88566872e-02,\n",
- " 7.80560193e-04, -6.31482676e-02, -2.33870205e-02, 7.95411617e-02,\n",
- " 4.28625084e-02, 1.11334838e-01, 2.69801039e-02, 4.53688316e-02,\n",
- " 4.04185504e-02, -3.17677244e-04, 7.20783696e-03, -9.30013806e-02,\n",
- " 1.43534765e-02, 1.29759777e-02, 3.04906187e-03, -6.32892922e-02,\n",
- " 5.51022515e-02, 4.95584682e-02, -6.17064163e-03, -1.49571579e-02,\n",
- " -6.23148354e-03, -5.75126894e-02, -2.08213869e-02, -1.52377700e-02,\n",
- " 5.67473529e-04, -2.79246550e-02, 2.51257280e-03, -5.07347006e-03,\n",
- " -5.63088283e-02, 1.59230027e-02, 2.88392715e-02, -5.49843833e-02,\n",
- " -5.60203334e-03, 3.99401598e-02, 6.48093224e-02, -6.40543830e-03,\n",
- " -6.71263691e-03, -1.47173703e-02, 6.91259876e-02, 1.01106744e-02,\n",
- " 8.96588434e-03, 1.19373994e-02, -4.90396209e-02, 1.32782515e-02,\n",
- " -4.02567489e-03, 1.04573481e-01, -2.48427875e-02, 5.14872139e-04,\n",
- " -3.58534940e-02, 2.18786281e-02, -2.03787908e-02, 1.48096830e-02,\n",
- " 5.18971756e-02, 9.51515324e-03, 5.82710244e-02, -4.26020138e-02,\n",
- " 3.05221099e-02, 1.06252832e-02, -5.44070676e-02, -2.27933470e-03,\n",
- " -5.20571470e-02, -2.34924932e-03, -9.36745014e-03, -3.53393564e-03,\n",
- " 2.94360928e-02, -1.62051637e-02, -2.58429069e-03, 8.59572086e-03,\n",
- " 9.85456035e-02, -4.06813994e-03, -9.81669594e-03, 2.96845790e-02,\n",
- " -1.81967150e-02, -3.60262692e-02, 5.98667152e-02, -1.33204237e-02,\n",
- " -1.12310341e-02, 1.17032500e-02, -6.58730641e-02, 6.35968000e-02,\n",
- " -3.82804796e-02, -6.04177490e-02, -3.11209876e-02, -3.76994285e-04,\n",
- " 8.21387321e-02, -9.24617145e-03, 5.46354800e-02, 1.73117984e-02,\n",
- " -7.31705967e-03, 1.14239678e-02, -2.78365258e-02, -2.49437820e-02,\n",
- " 5.76970261e-03, -6.48611933e-02, 4.13633659e-02, -1.07995747e-02,\n",
- " 1.43664340e-02, 4.29632775e-02, -5.39758317e-02, 6.81054518e-02,\n",
- " -2.32428405e-02, 2.36772150e-02, 9.12302267e-03, -2.85037532e-02,\n",
- " -1.37815652e-02, 1.78093296e-02, 4.09769528e-02, 3.06042787e-02,\n",
- " -1.88611485e-02, -4.30043451e-02, -5.78223802e-02, 1.58756018e-01,\n",
- " 1.14910915e-01, -4.35356013e-02, 2.68743373e-02, -1.09048048e-03,\n",
- " -2.87686009e-02, -1.64047617e-03, 3.19359638e-02, 2.48954445e-02,\n",
- " -1.23990010e-02, 3.14294361e-02, -7.31677264e-02, -3.09050083e-02,\n",
- " -1.52001921e-02, -3.50537673e-02, -2.89013106e-02, 5.68768233e-02,\n",
- " -8.29850137e-03, 4.27614152e-02, 5.41349202e-02, -2.34491602e-02,\n",
- " 4.22167890e-02, 1.80702135e-01, -9.88851301e-03, -6.69028657e-03,\n",
- " 1.87298236e-03, 4.52948362e-02, -1.46639356e-02, 7.09923804e-02,\n",
- " 1.67470463e-02, 8.74400735e-02, 3.06419358e-02, 2.96499953e-02,\n",
- " 2.49631256e-02, 2.53423844e-02, -5.37566245e-02, 1.18165061e-01,\n",
- " 8.59691277e-02, -2.78971884e-02, 7.66887739e-02, -2.11541122e-03,\n",
- " 6.71741441e-02, -1.70802157e-02, 6.51863366e-02, 5.86805381e-02,\n",
- " -2.22079717e-02, 1.63076483e-02, 1.41100856e-02, 1.23611214e-02,\n",
- " 7.34195858e-02, 8.40411708e-03, 9.90935117e-02, 2.63773762e-02,\n",
- " -1.27116833e-02, -8.97971354e-03, -2.09459085e-02, 6.08176477e-02,\n",
- " -1.18746888e-03, 3.99580225e-02, 8.41351449e-02, -9.63668525e-03,\n",
- " 2.67174114e-02, 7.48860687e-02, -3.24967913e-02, 3.43479012e-04,\n",
- " 8.97536501e-02, -4.50268649e-02, 1.06858090e-01, -1.56591460e-02,\n",
- " 3.47793195e-03, 3.63286920e-02, -1.38713447e-02, -4.79564518e-02,\n",
- " 2.20379997e-02, 6.63399547e-02, -2.90442556e-02, 7.96480253e-02,\n",
- " 3.53837162e-02, 9.35909059e-03, -3.40761207e-02, -1.66805387e-02,\n",
- " -1.02745913e-01, 4.20074444e-03, 4.63263206e-02, 8.31818208e-03,\n",
- " -1.11303357e-02, 7.81788379e-02, -1.38446996e-02, 2.09451746e-02,\n",
- " 2.73621920e-02, 2.00774856e-02, 2.62355618e-02, 1.47767095e-02,\n",
- " -1.49381673e-03, 3.17577906e-02, 3.74071263e-02, -2.29913555e-02,\n",
- " 2.83956099e-02, 4.30012643e-02, -3.62946764e-02, 4.23429683e-02,\n",
- " 6.86931331e-03, 1.39244888e-02, 7.39490986e-02, 2.42529958e-02,\n",
- " 1.25602549e-02, -1.13097753e-03, 3.42628919e-02, 6.55322596e-02,\n",
- " -3.10005918e-02, 2.08212323e-02, 2.20190454e-02, 3.65807265e-02,\n",
- " 4.32189330e-02, 1.00127216e-02, -2.34282408e-02, 1.44732073e-02,\n",
- " -2.86562126e-02, 2.07785168e-03, 8.00691452e-03, 6.26016129e-03,\n",
- " 4.25436720e-03, -5.28176092e-02, -2.07833014e-02, 1.32442834e-02,\n",
- " 1.43008316e-02, -5.16064279e-02, -3.00741941e-02, 1.02726504e-01,\n",
- " 3.64327384e-03, 2.10725497e-02, -2.13543512e-02, -1.85689311e-02,\n",
- " -1.37409586e-02, -4.03830260e-02, 3.84078696e-02, -3.88897862e-03,\n",
- " -3.83013976e-03, 4.64836881e-02, 3.15867807e-03, 1.52224768e-02,\n",
- " 4.75724116e-02, -3.71970646e-02, 1.21691868e-01, -2.07152404e-03,\n",
- " -4.34292853e-02, 4.59217392e-02, 4.99858707e-02, 2.13617459e-02,\n",
- " -1.40371518e-02, 3.68467011e-02, 4.66825441e-02, 5.22719808e-02,\n",
- " 4.75657508e-02, 4.92333174e-02, -1.37452316e-02, -2.16609649e-02,\n",
- " -2.94767469e-02, 4.42293733e-02, 8.05306900e-03, 4.30436768e-02,\n",
- " 3.09169367e-02, 3.03586153e-03, 8.86451360e-03, -3.94265838e-02,\n",
- " 1.20000526e-01, 2.64589302e-02, -2.56066266e-02, -1.50065199e-02,\n",
- " -8.73001385e-03, -3.80736887e-02, -1.99454520e-02, -2.24667136e-02,\n",
- " 2.54471060e-02, 3.95988300e-03, 1.71692669e-02, -4.31194939e-02,\n",
- " -1.60197006e-03, 2.43819486e-02, 4.53526378e-02, -2.83546317e-02,\n",
- " 9.47393849e-03, -3.63451727e-02, 1.63530111e-02, -1.12066017e-02,\n",
- " 2.79785451e-02, 6.31254027e-03, 6.13662861e-02, -2.91502401e-02,\n",
- " -1.66457873e-02, 2.59106364e-02, 7.37313256e-02, 1.88655537e-02,\n",
- " -6.76015299e-03, -2.85965055e-02, -2.67611053e-02, 4.74370010e-02,\n",
- " -1.00759260e-01, -2.02660244e-02, 1.15286455e-01, 1.88764278e-02,\n",
- " 4.86868322e-02, 8.55640247e-02, 1.58901196e-02, -5.47034182e-02,\n",
- " -2.01820005e-02, -8.08133278e-03, 2.71024983e-02, -7.08344672e-03,\n",
- " -5.78339584e-03, -1.78454095e-03, 3.73672135e-02, 3.49419340e-02,\n",
- " -3.14066373e-02, 9.58922203e-04, 6.65858015e-02, -2.86915414e-02,\n",
- " 6.48145676e-02, -3.96812633e-02, 4.42832857e-02, 2.44307215e-03,\n",
- " -1.19309081e-02, 6.93908781e-02, 2.15752772e-03, 9.38279331e-02,\n",
- " -1.81190092e-02, -2.43434869e-02, -1.22260107e-02, 2.06455011e-02,\n",
- " 5.23359403e-02, -8.87418818e-03, 1.30219441e-02, 1.11385882e-02,\n",
- " -2.42972486e-02, 4.37092073e-02, 1.93088856e-02, -4.12717238e-02,\n",
- " 1.78094488e-02, -1.78493857e-02, 6.71600318e-03, 1.90298017e-02,\n",
- " -6.09736249e-04, -3.15604098e-02, 4.05093320e-02, 1.47739397e-02,\n",
- " 1.19946711e-02, -2.71599237e-02, 1.22903377e-01, 3.89652932e-03,\n",
- " -3.17971967e-02, -1.36811659e-02, 2.24031508e-02, -3.82991508e-02,\n",
- " -1.72315706e-02, 6.69926479e-02, -3.46939429e-03, -7.96057358e-02,\n",
- " -1.18125556e-02, 4.37342338e-02, 2.38369852e-02, 2.50293631e-02,\n",
- " 8.80027339e-02, -2.60384511e-02, 5.19163646e-02, -2.43317289e-03,\n",
- " 3.32515351e-02, -2.72021419e-03, -3.76803577e-02, 3.42820249e-02,\n",
- " -2.82038152e-02, -4.90723811e-02, 2.82530282e-02, 1.51483063e-03,\n",
- " 4.85456213e-02, 3.26632410e-02, -2.92662419e-02, 5.17779253e-02,\n",
- " 8.03022161e-02, -1.56830996e-03, -7.67859071e-03, 7.35788643e-02,\n",
- " 3.50075997e-02, -2.54020113e-02, 2.33081076e-02, -1.40188616e-02,\n",
- " 8.33168477e-02, -6.59106579e-03, -7.54412338e-02, -2.65334975e-02,\n",
- " 4.89935093e-02, -2.13595778e-02, -2.37485021e-03, 5.08222356e-02,\n",
- " 4.21900628e-03, 5.56836203e-02, 1.33971078e-02, -9.59222764e-03,\n",
- " 1.63696967e-02, 5.50045259e-03, 1.25113986e-02, -6.30294997e-03,\n",
- " -7.76878595e-02, 4.29169973e-03, -3.96660082e-02, -5.40622324e-02,\n",
- " 2.15043407e-02, -4.61911410e-02, -2.37710383e-02, 6.53768256e-02,\n",
- " 9.67107620e-03, -3.84159246e-03, -1.90502293e-02, 1.57599207e-02,\n",
- " 3.54349576e-02, 6.99545890e-02, 4.94214483e-02, 4.20822985e-02],\n",
+ " [ 0.09738816, 0.03414803, -0.01174096, ..., -0.0211659 ,\n",
+ " 0.06476735, 0.04520336],\n",
+ " [-0.01204782, 0.01029883, -0.06347279, ..., 0.02969738,\n",
+ " 0.00037249, 0.0290717 ],\n",
+ " [ 0.00126231, -0.04087918, 0.10473223, ..., -0.02034807,\n",
+ " -0.05642996, -0.07601316]], dtype=float32),\n",
+ " array([ 3.62404361e-02, -1.00626852e-02, 4.12637144e-02, 3.20797749e-02,\n",
+ " 1.44391898e-02, 7.38113932e-03, -1.47408815e-02, -2.03356724e-02,\n",
+ " -6.35444075e-02, -5.27319824e-03, 1.55216577e-02, -5.78907691e-03,\n",
+ " -3.53744105e-02, 7.53003210e-02, -2.61838436e-02, -2.22598054e-02,\n",
+ " 5.79506494e-02, -3.18826847e-02, -2.47530583e-02, 1.05029881e-01,\n",
+ " 2.06424054e-02, -6.48392886e-02, 4.18120436e-03, -6.73092678e-02,\n",
+ " 7.26668239e-02, 2.95326710e-02, -7.25710252e-03, 4.85973731e-02,\n",
+ " 2.12896802e-02, -4.66828197e-02, -6.76735789e-02, -2.04142742e-02,\n",
+ " -1.00255329e-02, 3.23494114e-02, 3.22821811e-02, 4.59385104e-02,\n",
+ " -1.83302704e-02, 2.82562263e-02, 9.65547264e-02, -3.08037046e-02,\n",
+ " -5.39704808e-04, -1.30822752e-02, 6.52810000e-03, 6.65754825e-02,\n",
+ " -3.52044925e-02, 1.50782866e-02, 7.80642256e-02, 1.31267197e-02,\n",
+ " 1.57132708e-02, 5.37683144e-02, 5.86614152e-03, 6.83248937e-02,\n",
+ " -1.25571080e-02, 9.09804776e-02, 3.26567069e-02, -3.23863328e-02,\n",
+ " 8.01511481e-02, -3.05876639e-02, -1.57759956e-03, 3.78393270e-02,\n",
+ " 3.71554047e-02, -1.29131777e-02, -4.87277023e-02, -1.07762925e-02,\n",
+ " -2.09876467e-02, 8.56673997e-03, 3.97746712e-02, 6.75867312e-03,\n",
+ " -6.06726948e-03, 5.35547324e-02, 7.05790222e-02, -2.65304744e-02,\n",
+ " -4.51288149e-02, 6.38363585e-02, -9.52603854e-03, 1.45330233e-03,\n",
+ " -8.93903710e-03, 5.95269771e-03, 2.79099885e-02, 4.63010035e-02,\n",
+ " 6.75270408e-02, -2.56517343e-02, -2.41983365e-02, 3.87565233e-02,\n",
+ " -5.41877141e-03, 4.70031761e-02, 1.92833517e-03, 1.97432283e-02,\n",
+ " 6.72746226e-02, -9.00398660e-03, 8.93408358e-02, -3.06866262e-02,\n",
+ " 7.47415051e-02, 1.98360041e-01, 4.19779047e-02, 5.59929572e-02,\n",
+ " 1.30328741e-02, 1.03475731e-02, 2.21154261e-02, 1.72696374e-02,\n",
+ " -1.44563289e-02, 6.06088974e-02, 6.66785166e-02, 8.57741758e-03,\n",
+ " -2.39256825e-02, -2.51507852e-02, 3.17007564e-02, -3.08507979e-02,\n",
+ " -2.94589419e-02, -2.09891666e-02, -1.80575401e-02, 2.21390519e-02,\n",
+ " 5.87918088e-02, -2.00730730e-02, -2.18769833e-02, -3.56195085e-02,\n",
+ " -3.30189094e-02, 4.88770101e-03, 5.68647236e-02, -6.82985643e-03,\n",
+ " -7.87242409e-03, 1.37207815e-02, 4.14539613e-02, 1.56477839e-02,\n",
+ " 4.12817746e-02, -5.25973253e-02, 3.45030688e-02, 1.01849660e-01,\n",
+ " 9.63369459e-02, 3.40379700e-02, -3.28626558e-02, 2.21213624e-02,\n",
+ " -3.60815637e-02, 4.05892096e-02, 2.14739684e-02, -4.60625999e-02,\n",
+ " -2.53308546e-02, 8.13112929e-02, -1.03141582e-02, 1.81099083e-02,\n",
+ " 4.80216090e-03, 9.54976305e-02, 4.65104431e-02, -3.07451375e-02,\n",
+ " 2.87534930e-02, -8.42135027e-03, -1.95605047e-02, -1.81016121e-02,\n",
+ " -1.42204044e-02, 1.24290593e-01, 4.80321534e-02, 1.45884603e-02,\n",
+ " 4.24653012e-03, -7.81426728e-02, 4.93251195e-04, 4.20478135e-02,\n",
+ " -1.04194479e-02, 1.03717681e-03, -1.00145554e-02, -2.45791003e-02,\n",
+ " -4.30497713e-03, -1.49193276e-02, -3.47578265e-02, 9.87907350e-02,\n",
+ " -5.56080490e-02, 4.69516777e-02, 2.24938663e-03, 5.01990244e-02,\n",
+ " 1.31887300e-02, 4.00844067e-02, 2.36485042e-02, 8.32027420e-02,\n",
+ " -5.18666431e-02, -3.87804653e-03, 5.74752651e-02, 4.49384190e-02,\n",
+ " -3.12516838e-02, 6.05831444e-02, 8.19941014e-02, -1.28470603e-02,\n",
+ " 5.60543835e-02, 8.88850987e-02, 2.29592789e-02, 2.83987299e-02,\n",
+ " -2.81242989e-02, 4.26620990e-03, 4.22059409e-02, -2.52152905e-02,\n",
+ " 2.05573365e-02, -4.86270674e-02, 4.55118716e-02, 4.26988639e-02,\n",
+ " -1.84952449e-02, -1.66064836e-02, 9.55225900e-02, 2.23741420e-02,\n",
+ " -2.32352223e-02, 4.38059121e-02, 5.40804341e-02, 9.03786570e-02,\n",
+ " 2.40899064e-03, 5.57620823e-02, 4.80235815e-02, 9.24917217e-03,\n",
+ " -5.21255508e-02, 2.33643167e-02, 2.19764803e-02, 6.49938313e-03,\n",
+ " -6.92149159e-04, -3.00937854e-02, -1.30449433e-03, 2.81931907e-02,\n",
+ " 4.48884405e-02, 3.28095965e-02, 1.91940051e-02, -9.01335225e-05,\n",
+ " -1.74635686e-02, 1.71994157e-02, -3.19485087e-03, -1.76358037e-03,\n",
+ " -3.87320630e-02, 2.17137001e-02, 1.05084674e-02, -2.25138515e-02,\n",
+ " 1.24400482e-01, 2.18744762e-02, -9.17441305e-03, 6.83817938e-02,\n",
+ " 4.12715226e-02, -1.50918553e-03, 4.00556847e-02, 4.83260900e-02,\n",
+ " 1.08003682e-02, -4.38890979e-02, 8.75647217e-02, 6.00520372e-02,\n",
+ " 4.57753427e-02, 2.60185041e-02, -1.74120571e-02, -1.12312892e-02,\n",
+ " 1.80204250e-02, -2.63278596e-02, -1.50434785e-02, -1.52808335e-03,\n",
+ " -3.52254920e-02, -4.65776250e-02, 6.33136705e-02, 1.31335938e-02,\n",
+ " 4.12639193e-02, -1.74302515e-02, 5.66557210e-05, -9.68488306e-03,\n",
+ " -4.44719754e-02, 4.48269807e-02, 4.97215763e-02, -3.03618666e-02,\n",
+ " 8.88043270e-03, 2.39550006e-02, -2.85554472e-02, 1.96982566e-02,\n",
+ " -2.81877816e-02, 2.43887305e-02, 8.95657241e-02, 1.46840019e-02,\n",
+ " 3.08184419e-02, 1.26163559e-02, 2.08933782e-02, -6.78256229e-02,\n",
+ " -2.28499230e-02, 3.86739783e-02, -3.76365855e-02, 1.10298641e-01,\n",
+ " 2.33064592e-02, -7.23616686e-03, 1.45978564e-02, 6.17714087e-03,\n",
+ " 5.97122638e-03, 1.80544686e-02, -3.51207703e-02, 1.03918621e-02,\n",
+ " 5.05592674e-02, 5.23468889e-02, 3.59910205e-02, 7.59560242e-02,\n",
+ " -2.78860256e-02, 8.51415214e-04, 9.22083184e-02, -3.13983150e-02,\n",
+ " -4.20855498e-03, 1.07994294e-02, 5.82499104e-03, 2.28286609e-02,\n",
+ " 3.21466997e-02, 1.24475351e-02, -2.10767649e-02, 5.44328466e-02,\n",
+ " -3.38977426e-02, -3.79893975e-03, -2.32445123e-03, -2.67968010e-02,\n",
+ " 1.52044566e-02, 8.30217823e-03, -4.40196805e-02, 4.19422835e-02,\n",
+ " 4.48080264e-02, 1.76371131e-02, -3.03743910e-02, 4.51597106e-03,\n",
+ " -8.69407225e-03, -2.22311579e-02, -1.70584694e-02, 1.30021875e-03,\n",
+ " 8.73410050e-03, 1.68561488e-02, -1.53215230e-02, 3.84384836e-03,\n",
+ " 2.63451505e-02, 1.00488618e-01, 4.50635180e-02, -3.60507667e-02,\n",
+ " -3.94031219e-03, 5.95506839e-03, -6.35116547e-02, 7.91681185e-02,\n",
+ " 3.32451286e-03, 1.23457924e-01, 1.12611111e-02, 3.33598293e-02,\n",
+ " -1.33562684e-02, 7.64230490e-02, -2.76233978e-03, 6.56257477e-03,\n",
+ " -2.65942663e-02, -2.57141441e-02, -2.39609424e-02, -3.50626372e-02,\n",
+ " -2.18117516e-02, 2.64051766e-03, 1.46059031e-02, 3.36433165e-02,\n",
+ " -3.66571359e-02, -2.98993252e-02, -1.91366393e-03, -1.34593323e-02,\n",
+ " 9.15418789e-02, -3.60024087e-02, -2.03645322e-02, -4.39534634e-02,\n",
+ " 3.92233618e-02, 2.33720499e-03, 8.83152112e-02, 4.56317514e-02,\n",
+ " 6.03598217e-03, -1.79811474e-03, 5.08119725e-02, 3.59347314e-02,\n",
+ " -1.87190659e-02, 3.07187764e-03, -2.59583108e-02, 6.92972168e-03,\n",
+ " -3.96266803e-02, -4.89765173e-03, 4.14057262e-03, -1.76513456e-02,\n",
+ " -7.99908303e-03, 5.27810678e-02, -3.22450604e-03, -2.25886367e-02,\n",
+ " 7.86461532e-02, 1.51972957e-02, -4.69339862e-02, -2.30701230e-02,\n",
+ " -3.50237498e-03, -1.66427959e-02, 2.17091739e-02, 2.95300758e-03,\n",
+ " 1.92045849e-02, -1.48078166e-02, -3.83858681e-02, 4.84168977e-02,\n",
+ " 3.50758880e-02, -2.91970596e-02, 1.18743733e-01, 1.15353623e-02,\n",
+ " 4.45905104e-02, 1.20615542e-01, -4.72970447e-03, 1.05048465e-02,\n",
+ " -3.86959091e-02, 2.70572864e-02, -2.45867316e-02, 2.95775849e-02,\n",
+ " -5.16405003e-03, 4.65180427e-02, -4.58280593e-02, -5.21804802e-02,\n",
+ " -3.96645069e-03, -4.45237271e-02, 2.03569904e-02, 3.17483917e-02,\n",
+ " 1.40855210e-02, -5.86931244e-04, 2.17727348e-02, 1.47175174e-02,\n",
+ " 1.64685734e-02, -4.54700971e-03, 1.33894578e-01, -6.02849119e-04,\n",
+ " -4.50279360e-04, 5.91845699e-02, 1.18924137e-02, 4.55351956e-02,\n",
+ " -4.57217433e-02, -2.60089338e-02, -1.55850118e-02, 4.11818624e-02,\n",
+ " 4.44398820e-02, -2.19457094e-02, -6.60716835e-03, -1.09312655e-02,\n",
+ " 4.55060154e-02, 1.39478128e-02, -3.72533046e-04, -3.49408425e-02,\n",
+ " 6.91487268e-02, 5.02386726e-02, -3.16306613e-02, 1.53550440e-02,\n",
+ " 1.08032366e-02, 3.38654183e-02, -5.88489734e-02, -5.08560613e-02,\n",
+ " -3.61575037e-02, -5.77050187e-02, -1.80412177e-02, 1.61922157e-01,\n",
+ " -1.82975903e-02, 9.25256759e-02, 3.96507345e-02, -4.89264056e-02,\n",
+ " 3.56887393e-02, -3.13477241e-03, 1.09409010e-02, 2.27443017e-02,\n",
+ " -2.88771726e-02, -2.52982974e-02, 4.97358199e-03, -1.58914495e-02,\n",
+ " -1.74713433e-02, 9.40158591e-02, -3.46052833e-02, 8.42058286e-02,\n",
+ " 2.82897856e-02, -4.40645926e-02, -2.02626958e-02, 1.83478650e-03,\n",
+ " -1.93328895e-02, 1.94808766e-02, 2.18821913e-02, 2.29608640e-02,\n",
+ " -4.64285575e-02, 9.41406563e-02, -4.05656174e-02, -3.40872854e-02,\n",
+ " -5.87998293e-02, -2.39296723e-03, -6.20852504e-03, -2.47565228e-02,\n",
+ " -4.49138470e-02, 8.34232755e-03, 8.86583980e-03, 1.19990539e-02,\n",
+ " 3.39879245e-02, 7.17839971e-02, 3.08833178e-02, 3.66404019e-02,\n",
+ " 6.80502057e-02, 7.73759112e-02, -1.72424912e-02, 8.06045681e-02,\n",
+ " -2.79832426e-02, 5.62598780e-02, -2.51862258e-02, 6.62845299e-02,\n",
+ " 2.39826683e-02, 2.42049824e-02, 1.48134828e-02, -3.38776745e-02,\n",
+ " -1.76236127e-02, 6.44013584e-02, 4.20280658e-02, -4.98452224e-03,\n",
+ " -5.75387478e-02, -2.15854077e-03, -1.13331620e-02, 6.87643513e-02,\n",
+ " 1.95539147e-02, 3.23824324e-02, -8.66599083e-02, 2.84758098e-02,\n",
+ " 1.65818371e-02, -1.10938782e-02, 2.29168367e-02, -1.51646733e-02,\n",
+ " 7.75221810e-02, 1.09356128e-01, 3.95860337e-02, -4.40029688e-02,\n",
+ " -1.07184742e-02, -5.75669669e-03, 3.60427238e-02, -6.05419930e-03],\n",
" dtype=float32)]"
]
},
- "execution_count": 19,
+ "execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
@@ -748,7 +732,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
@@ -765,7 +749,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
@@ -778,7 +762,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
@@ -797,14 +781,14 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step\n"
+ "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step\n"
]
}
],
@@ -814,7 +798,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
@@ -826,16 +810,16 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "0.8903"
+ "0.886"
]
},
- "execution_count": 25,
+ "execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
@@ -848,23 +832,23 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[[819 4 12 34 6 5 114 0 6 0]\n",
- " [ 1 993 1 3 0 0 2 0 0 0]\n",
- " [ 11 2 782 7 146 0 47 0 5 0]\n",
- " [ 10 35 9 896 32 1 16 0 1 0]\n",
- " [ 2 7 35 21 880 1 52 0 2 0]\n",
- " [ 0 0 0 0 0 962 0 23 5 10]\n",
- " [105 6 66 37 82 0 698 0 6 0]\n",
- " [ 0 0 0 0 0 14 0 968 1 17]\n",
- " [ 2 1 4 2 3 2 8 2 975 1]\n",
- " [ 1 0 0 0 0 11 0 55 3 930]]\n"
+ "[[887 0 19 10 0 8 67 0 8 1]\n",
+ " [ 1 988 1 5 0 1 4 0 0 0]\n",
+ " [ 19 0 806 10 40 2 119 0 4 0]\n",
+ " [ 29 12 20 894 19 1 21 0 4 0]\n",
+ " [ 1 2 153 20 735 0 87 1 1 0]\n",
+ " [ 0 0 0 0 0 955 1 27 2 15]\n",
+ " [179 1 58 25 28 0 700 0 9 0]\n",
+ " [ 0 0 0 0 0 9 0 960 0 31]\n",
+ " [ 1 0 2 2 2 5 9 1 977 1]\n",
+ " [ 0 0 0 0 0 6 0 36 0 958]]\n"
]
}
],
@@ -877,12 +861,12 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
@@ -911,10 +895,310 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 27,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(28, 28)"
+ ]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "X_train.iloc[0].to_numpy().reshape(28,28).shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(60000, 784)"
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "X_train.shape"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "arr = X_train.to_numpy()\n",
+ "arr = arr.reshape(60000, 28,28)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(60000, 28, 28)"
+ ]
+ },
+ "execution_count": 30,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "arr.shape"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "* 0 T-shirt/top\n",
+ "* 1 Trouser\n",
+ "* 2 Pullover\n",
+ "* 3 Dress\n",
+ "* 4 Coat\n",
+ "* 5 Sandal\n",
+ "* 6 Shirt\n",
+ "* 7 Sneaker\n",
+ "* 8 Bag\n",
+ "* 9 Ankle boot"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 1.])"
+ ]
+ },
+ "execution_count": 38,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "y_train[1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.image.AxesImage at 0x7f2148d44390>"
+ ]
+ },
+ "execution_count": 37,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": "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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.imshow(arr[1], cmap='Greys')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "9"
+ ]
+ },
+ "execution_count": 39,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "sample = X_train.iloc[1].to_numpy()\n",
+ "sample = np.array([sample])\n",
+ "out = model.predict(sample)\n",
+ "out.argmax()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "ARR[900] - 28x28"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 172,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from random import gauss\n",
+ "\n",
+ "def checkNoisyImage():\n",
+ " item = arr[1].copy()\n",
+ "\n",
+ " for i in range(0, len(item)):\n",
+ " for x in range(0, len(arr[1][i])):\n",
+ " item[i][x] = arr[1][i][x] * abs(random.uniform(.7,1.3))\n",
+ " \n",
+ " item = item.reshape(1,784)\n",
+ " out = model.predict(item, verbose=0)\n",
+ " if out.argmax() != 9:\n",
+ " return (True, item, out.argmax())\n",
+ " else:\n",
+ " return (False, '', out.argmax())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 179,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([ 0, 0, 0, 0, 0, 0, 0, 0, 48, 161, 218, 171, 147,\n",
+ " 116, 185, 235, 201, 209, 203, 204, 220, 208, 126, 133, 162, 164,\n",
+ " 187, 0])"
+ ]
+ },
+ "execution_count": 179,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "arr[1][15]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 197,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "9\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.image.AxesImage at 0x7f210519c950>"
+ ]
+ },
+ "execution_count": 197,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": "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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "item = arr[1].copy()\n",
+ "\n",
+ "item[15][8] = 60\n",
+ "item[15][9] = 150\n",
+ "item[15][10] = 230\n",
+ "item[15][11] = 140\n",
+ "item[15][12] = 160\n",
+ "item[15][13] = 130\n",
+ "item[15][14] = 200\n",
+ "item[15][15] = 210\n",
+ "\n",
+ "item = item.reshape(1,784)\n",
+ "out = model.predict(item, verbose=0)\n",
+ "print(out.argmax())\n",
+ "item = item.reshape(28,28)\n",
+ "plt.imshow(item, cmap='Greys')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 173,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "7\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": "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",
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "found = False\n",
+ "\n",
+ "while found == False:\n",
+ " returned = checkNoisyImage()\n",
+ " found = returned[0]\n",
+ " item = returned[1]\n",
+ " val = returned[2]\n",
+ "\n",
+ "item = item.reshape(28,28)\n",
+ "plt.imshow(item, cmap='Greys')\n",
+ "print(val)"
+ ]
}
],
"metadata": {
diff --git a/trickAIImageDetection/TrickImageDetection.ipynb b/trickAIImageDetection/TrickImageDetection.ipynb
@@ -0,0 +1,109 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 171,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from PIL import Image, ImageFilter\n",
+ "import random\n",
+ "from random import gauss\n",
+ "\n",
+ "img = Image.open('img/AiImage.png')\n",
+ "img = img.convert('RGB')\n",
+ "img = img.crop(box=(250, 0, 950, 550))\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "def rndNoise():\n",
+ " return round(gauss(0,2))\n",
+ "\n",
+ "\n",
+ "\n",
+ "img = img.filter(ImageFilter.SHARPEN)\n",
+ "img = img.filter(ImageFilter.SHARPEN)\n",
+ "img = img.filter(ImageFilter.SHARPEN)\n",
+ "\n",
+ "pixels = img.load() # Pixel map\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "img.save('img/ManipulatedImg.png')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 172,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(550, 700, 3)"
+ ]
+ },
+ "execution_count": 172,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "arr = np.array(img)\n",
+ "arr.shape"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "* 1400 = x\n",
+ "* 933 = y"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 173,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(700, 3)"
+ ]
+ },
+ "execution_count": 173,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "arr[0].shape"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": ".venv",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
