machinelearning

Unnamed repository; edit this file 'description' to name the repository.
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commit 1e43f95068ac8e9cad64d379ba4691291b1d18cf
parent 721b00bbb65ccf75b83780b48abcf49ad1f10181
Author: Andrew <andrewlaack1@gmail.com>
Date:   Fri, 25 Oct 2024 18:13:58 -0500

Moved things

Diffstat:

DcatIdentifier/CatOrDogIdentifierCNN.ipynb | 347-------------------------------------------------------------------------------


AcatsAndDogs/CatDiffuser.ipynb | 303+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++


AcatsAndDogs/CatOrDogIdentifierCNN.ipynb | 7888+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++


MtrickAIImageDetection/TrickImageDetection.ipynb | 2+-


4 files changed, 8192 insertions(+), 348 deletions(-)

diff --git a/catIdentifier/CatOrDogIdentifierCNN.ipynb b/catIdentifier/CatOrDogIdentifierCNN.ipynb
@@ -1,347 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Dataset From:\n",
-    "\n",
-    "https://www.kaggle.com/datasets/tongpython/cat-and-dog"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import keras\n",
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from PIL import Image\n",
-    "import os\n",
-    "\n",
-    "\n",
-    "def load_image_numpy(img_path):\n",
-    "    image = Image.open(img_path)\n",
-    "    image = image.resize((150,150))\n",
-    "    img_arr = np.array(image)\n",
-    "    img_arr = img_arr / 255.0\n",
-    "    return img_arr\n",
-    "\n",
-    "\n",
-    "catPaths = os.listdir('../datasets/catVsDogImages/cats')\n",
-    "for i in range(0, len(catPaths)):\n",
-    "    catPaths[i] = '../datasets/catVsDogImages/cats/' + catPaths[i]\n",
-    "\n",
-    "\n",
-    "catImgs = []\n",
-    "for i in catPaths:\n",
-    "    catImgs.append(load_image_numpy(i))\n",
-    "\n",
-    "dogPaths = os.listdir('../datasets/catVsDogImages/dogs')\n",
-    "for i in range(0, len(dogPaths)):\n",
-    "    dogPaths[i] = '../datasets/catVsDogImages/dogs/' + dogPaths[i]\n",
-    "\n",
-    "\n",
-    "dogImgs = []\n",
-    "for i in dogPaths:\n",
-    "    dogImgs.append(load_image_numpy(i))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "X = np.array(catImgs + dogImgs)\n",
-    "y = np.array([0] * len(catImgs) + [1] * len(dogImgs))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7f0482621d90>"
-      ]
-     },
-     "execution_count": 45,
-     "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(X[2000])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.model_selection import train_test_split\n",
-    "\n",
-    "X_train, X_test, y_train, y_test = train_test_split(X,y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "X_train = X_train.reshape(X_train.shape[0], -1)\n",
-    "X_test = X_test.reshape(X_test.shape[0], -1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.decomposition import PCA\n",
-    "\n",
-    "pca = PCA(n_components=.95)\n",
-    "\n",
-    "X_train = pca.fit_transform(X_train)\n",
-    "X_test = pca.transform(X_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(506, 476)"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_test.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(1517, 476)"
-      ]
-     },
-     "execution_count": 50,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_train.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.preprocessing import StandardScaler\n",
-    "std = StandardScaler()\n",
-    "X_train = std.fit_transform(X_train)\n",
-    "X_test = std.transform(X_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model = keras.Sequential([\n",
-    "    keras.layers.Input(shape=X_train[0].shape),\n",
-    "    keras.layers.Dense(512, activation='relu'),\n",
-    "    keras.layers.Dropout(.3),\n",
-    "    keras.layers.Dense(512, activation='relu'),\n",
-    "    keras.layers.BatchNormalization(),\n",
-    "    keras.layers.Dense(256, activation='relu'),\n",
-    "    keras.layers.Dropout(.3),\n",
-    "    keras.layers.Dense(256, activation='relu'),\n",
-    "    keras.layers.BatchNormalization(),\n",
-    "    keras.layers.Dropout(.3),\n",
-    "    keras.layers.Dense(128, activation='relu'),\n",
-    "    keras.layers.Dropout(.3),\n",
-    "    keras.layers.Dense(128, activation='relu'),\n",
-    "    keras.layers.Dense(1, activation='sigmoid')\n",
-    "])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Epoch 1/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 7ms/step - accuracy: 0.9560 - loss: 0.1256 - val_accuracy: 0.5613 - val_loss: 1.3363\n",
-      "Epoch 2/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9679 - loss: 0.1166 - val_accuracy: 0.6067 - val_loss: 1.1412\n",
-      "Epoch 3/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step - accuracy: 0.9731 - loss: 0.0962 - val_accuracy: 0.5929 - val_loss: 1.7505\n",
-      "Epoch 4/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9672 - loss: 0.0971 - val_accuracy: 0.5889 - val_loss: 1.5622\n",
-      "Epoch 5/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9646 - loss: 0.0917 - val_accuracy: 0.6067 - val_loss: 1.6817\n",
-      "Epoch 6/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9514 - loss: 0.1217 - val_accuracy: 0.6107 - val_loss: 1.6093\n",
-      "Epoch 7/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9658 - loss: 0.0948 - val_accuracy: 0.5810 - val_loss: 1.6161\n",
-      "Epoch 8/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9556 - loss: 0.1239 - val_accuracy: 0.5850 - val_loss: 1.9338\n",
-      "Epoch 9/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step - accuracy: 0.9754 - loss: 0.0816 - val_accuracy: 0.5791 - val_loss: 1.6988\n",
-      "Epoch 10/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9667 - loss: 0.1137 - val_accuracy: 0.5771 - val_loss: 1.7474\n",
-      "Epoch 11/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9719 - loss: 0.0750 - val_accuracy: 0.5711 - val_loss: 1.9768\n",
-      "Epoch 12/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step - accuracy: 0.9626 - loss: 0.0972 - val_accuracy: 0.5494 - val_loss: 1.6728\n",
-      "Epoch 13/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9688 - loss: 0.0977 - val_accuracy: 0.5830 - val_loss: 1.9562\n",
-      "Epoch 14/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9641 - loss: 0.0987 - val_accuracy: 0.5613 - val_loss: 1.5024\n",
-      "Epoch 15/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9736 - loss: 0.0750 - val_accuracy: 0.5751 - val_loss: 1.8563\n",
-      "Epoch 16/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step - accuracy: 0.9733 - loss: 0.0842 - val_accuracy: 0.5751 - val_loss: 1.5326\n",
-      "Epoch 17/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9607 - loss: 0.1385 - val_accuracy: 0.5889 - val_loss: 1.4378\n",
-      "Epoch 18/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9717 - loss: 0.0927 - val_accuracy: 0.5711 - val_loss: 1.8147\n",
-      "Epoch 19/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9839 - loss: 0.0491 - val_accuracy: 0.5474 - val_loss: 1.3703\n",
-      "Epoch 20/20\n",
-      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 5ms/step - accuracy: 0.9801 - loss: 0.0766 - val_accuracy: 0.5613 - val_loss: 1.7405\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<keras.src.callbacks.history.History at 0x7f04ece6fb90>"
-      ]
-     },
-     "execution_count": 59,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "model.fit(x=X_train, y=y_train, batch_size=10, epochs=20, validation_data=(X_test,y_test))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[1m16/16\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 1ms/step \n",
-      "Accuracy: 0.5770750988142292\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sklearn.metrics import accuracy_score\n",
-    "\n",
-    "y_pred = model.predict(X_test)\n",
-    "\n",
-    "y_predictions = []\n",
-    "for i in y_pred:\n",
-    "    y_predictions.append(round(i[0]))\n",
-    "\n",
-    "\n",
-    "accuracy = accuracy_score(y_pred=y_predictions, y_true=y_test)\n",
-    "\n",
-    "print(f\"Accuracy: {accuracy}\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "y_predictions"
-   ]
-  }
- ],
- "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
-}
diff --git a/catsAndDogs/CatDiffuser.ipynb b/catsAndDogs/CatDiffuser.ipynb
@@ -0,0 +1,303 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "FAILED PROJECT!!!\n",
+    "\n",
+    "TOO LONG TO TRAIN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import keras\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from PIL import Image\n",
+    "import os\n",
+    "\n",
+    "\n",
+    "def load_image_numpy(img_path):\n",
+    "    image = Image.open(img_path)\n",
+    "    image = image.resize((300,300))\n",
+    "    img_arr = np.array(image)\n",
+    "    img_arr = img_arr / 255.0\n",
+    "    return img_arr\n",
+    "\n",
+    "\n",
+    "catPaths = os.listdir('../datasets/catVsDogImages/cats')\n",
+    "for i in range(0, len(catPaths)):\n",
+    "    catPaths[i] = '../datasets/catVsDogImages/cats/' + catPaths[i]\n",
+    "\n",
+    "\n",
+    "catImgs = []\n",
+    "for i in catPaths:\n",
+    "    catImgs.append(load_image_numpy(i))\n",
+    "\n",
+    "\n",
+    "X = np.array(catImgs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Steps:\n",
+    "\n",
+    "1. Create random noise of proper size\n",
+    "2. Apply this to an image and this becomes X\n",
+    "3. y becomes the random noise\n",
+    "4. Create a network to predict the noise\n",
+    "5. Send random noise into the network repatedly until we get a new image, each time removing the output of the network from the input."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1011, 300, 300, 3)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "y_1 = np.random.normal(0, .3, (1011, 300, 300, 3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_with_noise = X + y_1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_in_with_noise = X_with_noise.copy()\n",
+    "y_2 = np.random.normal(0, .3, (1011, 300, 300, 3))\n",
+    "y_3 = np.random.normal(0, .3, (1011, 300, 300, 3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_with_noise_2 = X_in_with_noise + y_2\n",
+    "X_with_noise_3 = X_with_noise_2.copy() + y_3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-10-24 23:33:10.279380: 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 23:33:10.279825: 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"
+     ]
+    }
+   ],
+   "source": [
+    "model = keras.Sequential([\n",
+    "    keras.layers.Input(shape=(300, 300, 3)),\n",
+    "    \n",
+    "    keras.layers.Conv2D(32, (3, 3), activation='relu', padding='same'),  # (300, 300, 32)\n",
+    "    keras.layers.MaxPooling2D(pool_size=(2, 2)),  # (150, 150, 32)\n",
+    "    \n",
+    "    keras.layers.Conv2D(64, (3, 3), activation='relu', padding='same'),  # (150, 150, 64)\n",
+    "    keras.layers.MaxPooling2D(pool_size=(2, 2)),  # (75, 75, 64)\n",
+    "\n",
+    "    keras.layers.Conv2D(128, (3, 3), activation='relu', padding='same'),  # (75, 75, 128)\n",
+    "\n",
+    "    keras.layers.Conv2DTranspose(64, (3, 3), strides=(2, 2), activation='relu', padding='same'),  # (75, 75, 64)\n",
+    "    keras.layers.Conv2DTranspose(32, (3, 3), strides=(2, 2), activation='relu', padding='same'),  # (150, 150, 32)\n",
+    "    \n",
+    "    keras.layers.Conv2D(3, (3, 3), activation='sigmoid', padding='same')  # (150, 150, 3)\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.compile(loss='mse', optimizer='adam')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(300, 300, 3)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X[0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/30\n",
+      "\u001b[1m21/21\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m90s\u001b[0m 4s/step - loss: 0.2274\n",
+      "Epoch 2/30\n",
+      "\u001b[1m21/21\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m141s\u001b[0m 4s/step - loss: 0.0900\n",
+      "Epoch 3/30\n",
+      "\u001b[1m17/21\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m16s\u001b[0m 4s/step - loss: 0.0900"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_with_noise\u001b[49m\u001b[43m,\u001b[49m\u001b[43my_1\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m30\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m50\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/keras/src/utils/traceback_utils.py:117\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    115\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    116\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 117\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    118\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    119\u001b[0m     filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/keras/src/backend/tensorflow/trainer.py:314\u001b[0m, in \u001b[0;36mTensorFlowTrainer.fit\u001b[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq)\u001b[0m\n\u001b[1;32m    312\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step, iterator \u001b[38;5;129;01min\u001b[39;00m epoch_iterator\u001b[38;5;241m.\u001b[39menumerate_epoch():\n\u001b[1;32m    313\u001b[0m     callbacks\u001b[38;5;241m.\u001b[39mon_train_batch_begin(step)\n\u001b[0;32m--> 314\u001b[0m     logs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    315\u001b[0m     logs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pythonify_logs(logs)\n\u001b[1;32m    316\u001b[0m     callbacks\u001b[38;5;241m.\u001b[39mon_train_batch_end(step, logs)\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/util/traceback_utils.py:150\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    148\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    149\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 150\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    152\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py:833\u001b[0m, in \u001b[0;36mFunction.__call__\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m    830\u001b[0m compiler \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mxla\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnonXla\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    832\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m OptionalXlaContext(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_jit_compile):\n\u001b[0;32m--> 833\u001b[0m   result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    835\u001b[0m new_tracing_count \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexperimental_get_tracing_count()\n\u001b[1;32m    836\u001b[0m without_tracing \u001b[38;5;241m=\u001b[39m (tracing_count \u001b[38;5;241m==\u001b[39m new_tracing_count)\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/polymorphic_function/polymorphic_function.py:878\u001b[0m, in \u001b[0;36mFunction._call\u001b[0;34m(self, *args, **kwds)\u001b[0m\n\u001b[1;32m    875\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock\u001b[38;5;241m.\u001b[39mrelease()\n\u001b[1;32m    876\u001b[0m \u001b[38;5;66;03m# In this case we have not created variables on the first call. So we can\u001b[39;00m\n\u001b[1;32m    877\u001b[0m \u001b[38;5;66;03m# run the first trace but we should fail if variables are created.\u001b[39;00m\n\u001b[0;32m--> 878\u001b[0m results \u001b[38;5;241m=\u001b[39m \u001b[43mtracing_compilation\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_function\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    879\u001b[0m \u001b[43m    \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_variable_creation_config\u001b[49m\n\u001b[1;32m    880\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    881\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_created_variables:\n\u001b[1;32m    882\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCreating variables on a non-first call to a function\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    883\u001b[0m                    \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m decorated with tf.function.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/polymorphic_function/tracing_compilation.py:139\u001b[0m, in \u001b[0;36mcall_function\u001b[0;34m(args, kwargs, tracing_options)\u001b[0m\n\u001b[1;32m    137\u001b[0m bound_args \u001b[38;5;241m=\u001b[39m function\u001b[38;5;241m.\u001b[39mfunction_type\u001b[38;5;241m.\u001b[39mbind(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    138\u001b[0m flat_inputs \u001b[38;5;241m=\u001b[39m function\u001b[38;5;241m.\u001b[39mfunction_type\u001b[38;5;241m.\u001b[39munpack_inputs(bound_args)\n\u001b[0;32m--> 139\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunction\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_flat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# pylint: disable=protected-access\u001b[39;49;00m\n\u001b[1;32m    140\u001b[0m \u001b[43m    \u001b[49m\u001b[43mflat_inputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcaptured_inputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfunction\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcaptured_inputs\u001b[49m\n\u001b[1;32m    141\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/polymorphic_function/concrete_function.py:1322\u001b[0m, in \u001b[0;36mConcreteFunction._call_flat\u001b[0;34m(self, tensor_inputs, captured_inputs)\u001b[0m\n\u001b[1;32m   1318\u001b[0m possible_gradient_type \u001b[38;5;241m=\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPossibleTapeGradientTypes(args)\n\u001b[1;32m   1319\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (possible_gradient_type \u001b[38;5;241m==\u001b[39m gradients_util\u001b[38;5;241m.\u001b[39mPOSSIBLE_GRADIENT_TYPES_NONE\n\u001b[1;32m   1320\u001b[0m     \u001b[38;5;129;01mand\u001b[39;00m executing_eagerly):\n\u001b[1;32m   1321\u001b[0m   \u001b[38;5;66;03m# No tape is watching; skip to running the function.\u001b[39;00m\n\u001b[0;32m-> 1322\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_inference_function\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_preflattened\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1323\u001b[0m forward_backward \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_select_forward_and_backward_functions(\n\u001b[1;32m   1324\u001b[0m     args,\n\u001b[1;32m   1325\u001b[0m     possible_gradient_type,\n\u001b[1;32m   1326\u001b[0m     executing_eagerly)\n\u001b[1;32m   1327\u001b[0m forward_function, args_with_tangents \u001b[38;5;241m=\u001b[39m forward_backward\u001b[38;5;241m.\u001b[39mforward()\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/polymorphic_function/atomic_function.py:216\u001b[0m, in \u001b[0;36mAtomicFunction.call_preflattened\u001b[0;34m(self, args)\u001b[0m\n\u001b[1;32m    214\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcall_preflattened\u001b[39m(\u001b[38;5;28mself\u001b[39m, args: Sequence[core\u001b[38;5;241m.\u001b[39mTensor]) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Any:\n\u001b[1;32m    215\u001b[0m \u001b[38;5;250m  \u001b[39m\u001b[38;5;124;03m\"\"\"Calls with flattened tensor inputs and returns the structured output.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 216\u001b[0m   flat_outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_flat\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    217\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfunction_type\u001b[38;5;241m.\u001b[39mpack_output(flat_outputs)\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/polymorphic_function/atomic_function.py:251\u001b[0m, in \u001b[0;36mAtomicFunction.call_flat\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m    249\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m record\u001b[38;5;241m.\u001b[39mstop_recording():\n\u001b[1;32m    250\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_bound_context\u001b[38;5;241m.\u001b[39mexecuting_eagerly():\n\u001b[0;32m--> 251\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_bound_context\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcall_function\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    252\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    253\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    254\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunction_type\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mflat_outputs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    255\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    256\u001b[0m   \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    257\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m make_call_op_in_graph(\n\u001b[1;32m    258\u001b[0m         \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    259\u001b[0m         \u001b[38;5;28mlist\u001b[39m(args),\n\u001b[1;32m    260\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_bound_context\u001b[38;5;241m.\u001b[39mfunction_call_options\u001b[38;5;241m.\u001b[39mas_attrs(),\n\u001b[1;32m    261\u001b[0m     )\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/context.py:1500\u001b[0m, in \u001b[0;36mContext.call_function\u001b[0;34m(self, name, tensor_inputs, num_outputs)\u001b[0m\n\u001b[1;32m   1498\u001b[0m cancellation_context \u001b[38;5;241m=\u001b[39m cancellation\u001b[38;5;241m.\u001b[39mcontext()\n\u001b[1;32m   1499\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cancellation_context \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1500\u001b[0m   outputs \u001b[38;5;241m=\u001b[39m \u001b[43mexecute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexecute\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1501\u001b[0m \u001b[43m      \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mutf-8\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1502\u001b[0m \u001b[43m      \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnum_outputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1503\u001b[0m \u001b[43m      \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtensor_inputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1504\u001b[0m \u001b[43m      \u001b[49m\u001b[43mattrs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1505\u001b[0m \u001b[43m      \u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1506\u001b[0m \u001b[43m  \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1507\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1508\u001b[0m   outputs \u001b[38;5;241m=\u001b[39m execute\u001b[38;5;241m.\u001b[39mexecute_with_cancellation(\n\u001b[1;32m   1509\u001b[0m       name\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mutf-8\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m   1510\u001b[0m       num_outputs\u001b[38;5;241m=\u001b[39mnum_outputs,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1514\u001b[0m       cancellation_manager\u001b[38;5;241m=\u001b[39mcancellation_context,\n\u001b[1;32m   1515\u001b[0m   )\n",
+      "File \u001b[0;32m~/gitRepos/machineLearning/.venv/lib/python3.11/site-packages/tensorflow/python/eager/execute.py:53\u001b[0m, in \u001b[0;36mquick_execute\u001b[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[1;32m     51\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m     52\u001b[0m   ctx\u001b[38;5;241m.\u001b[39mensure_initialized()\n\u001b[0;32m---> 53\u001b[0m   tensors \u001b[38;5;241m=\u001b[39m \u001b[43mpywrap_tfe\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTFE_Py_Execute\u001b[49m\u001b[43m(\u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_handle\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mop_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     54\u001b[0m \u001b[43m                                      \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum_outputs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     55\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m core\u001b[38;5;241m.\u001b[39m_NotOkStatusException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m     56\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m name \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "model.fit(X_with_noise,y_1, epochs=30, batch_size=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.save(filepath='../models/CatDifuse.keras', overwrite=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.fit(X_with_noise_2,y_2, epochs=30, batch_size=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.save(filepath='../models/CatDifuse.keras', overwrite=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.fit(X_with_noise_3,y_3, epochs=30, batch_size=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.save(filepath='../models/CatDifuse.keras', overwrite=True)"
+   ]
+  }
+ ],
+ "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
+}
diff --git a/catsAndDogs/CatOrDogIdentifierCNN.ipynb b/catsAndDogs/CatOrDogIdentifierCNN.ipynb
@@ -0,0 +1,7888 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset From:\n",
+    "\n",
+    "https://www.kaggle.com/datasets/tongpython/cat-and-dog"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import keras\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from PIL import Image\n",
+    "import os\n",
+    "\n",
+    "\n",
+    "def load_image_numpy(img_path):\n",
+    "    image = Image.open(img_path)\n",
+    "    image = image.resize((150,150))\n",
+    "    img_arr = np.array(image)\n",
+    "    img_arr = img_arr / 255.0\n",
+    "    return img_arr\n",
+    "\n",
+    "\n",
+    "catPaths = os.listdir('../datasets/catVsDogImages/cats')\n",
+    "for i in range(0, len(catPaths)):\n",
+    "    catPaths[i] = '../datasets/catVsDogImages/cats/' + catPaths[i]\n",
+    "\n",
+    "\n",
+    "catImgs = []\n",
+    "for i in catPaths:\n",
+    "    catImgs.append(load_image_numpy(i))\n",
+    "\n",
+    "dogPaths = os.listdir('../datasets/catVsDogImages/dogs')\n",
+    "for i in range(0, len(dogPaths)):\n",
+    "    dogPaths[i] = '../datasets/catVsDogImages/dogs/' + dogPaths[i]\n",
+    "\n",
+    "\n",
+    "dogImgs = []\n",
+    "for i in dogPaths:\n",
+    "    dogImgs.append(load_image_numpy(i))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = np.array(catImgs + dogImgs)\n",
+    "y = np.array([0] * len(catImgs) + [1] * len(dogImgs))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x7f916b959c50>"
+      ]
+     },
+     "execution_count": 42,
+     "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(X[2000])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X,y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train = X_train.reshape(X_train.shape[0], -1)\n",
+    "X_test = X_test.reshape(X_test.shape[0], -1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.manifold import TSNE\n",
+    "tsne = TSNE(n_components=3, max_iter=1000)\n",
+    "\n",
+    "out = tsne.fit_transform(X_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "x=%{x}<br>y=%{y}<br>z=%{z}<br>color=%{marker.color}<extra></extra>",
+         "legendgroup": "",
+         "marker": {
+          "color": [
+           0,
+           1,
+           1,
+           1,
+           1,
+           0,
+           1,
+           1,
+           1,
+           1,
+           0,
+           1,
+           1,
+           0,
+           1,
+           1,
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+           1,
+           0,
+           1,
+           1,
+           1,
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+           1,
+           0,
+           0,
+           0,
+           1,
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+           0,
+           0,
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+           0,
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+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
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+           "zaxis": {
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+            "gridcolor": "white",
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+            "ticks": "",
+            "zerolinecolor": "white"
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+          },
+          "shapedefaults": {
+           "line": {
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+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import plotly.express as px\n",
+    "\n",
+    "fig = px.scatter_3d(x=out[:,0], y=out[:,1], z=out[:,2], color=y_train)\n",
+    "fig.update_traces(marker=dict(size=2))\n",
+    "fig.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(506, 67500)"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_test.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1517, 67500)"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import StandardScaler\n",
+    "std = StandardScaler()\n",
+    "X_train = std.fit_transform(X_train)\n",
+    "X_test = std.transform(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-10-24 21:10:52.202257: 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 21:10:52.202708: 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"
+     ]
+    }
+   ],
+   "source": [
+    "model = keras.Sequential([\n",
+    "    keras.layers.Input(shape=X_train[0].shape),\n",
+    "    keras.layers.Dense(512, activation='relu'),\n",
+    "    keras.layers.Dropout(.3),\n",
+    "    keras.layers.Dense(512, activation='relu'),\n",
+    "    keras.layers.BatchNormalization(),\n",
+    "    keras.layers.Dense(256, activation='relu'),\n",
+    "    keras.layers.Dropout(.3),\n",
+    "    keras.layers.Dense(256, activation='relu'),\n",
+    "    keras.layers.BatchNormalization(),\n",
+    "    keras.layers.Dropout(.3),\n",
+    "    keras.layers.Dense(128, activation='relu'),\n",
+    "    keras.layers.Dropout(.3),\n",
+    "    keras.layers.Dense(128, activation='relu'),\n",
+    "    keras.layers.Dense(1, activation='sigmoid')\n",
+    "])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 202ms/step - accuracy: 0.7867 - loss: 0.4650 - val_accuracy: 0.6206 - val_loss: 0.7092\n",
+      "Epoch 2/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 200ms/step - accuracy: 0.7559 - loss: 0.4859 - val_accuracy: 0.5692 - val_loss: 0.8605\n",
+      "Epoch 3/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 200ms/step - accuracy: 0.7854 - loss: 0.4530 - val_accuracy: 0.5870 - val_loss: 0.8507\n",
+      "Epoch 4/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 200ms/step - accuracy: 0.7995 - loss: 0.4389 - val_accuracy: 0.5415 - val_loss: 0.8822\n",
+      "Epoch 5/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 200ms/step - accuracy: 0.7924 - loss: 0.4668 - val_accuracy: 0.5968 - val_loss: 0.9393\n",
+      "Epoch 6/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 200ms/step - accuracy: 0.8178 - loss: 0.4114 - val_accuracy: 0.6186 - val_loss: 0.8245\n",
+      "Epoch 7/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 200ms/step - accuracy: 0.8119 - loss: 0.3997 - val_accuracy: 0.6028 - val_loss: 0.8350\n",
+      "Epoch 8/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 201ms/step - accuracy: 0.8123 - loss: 0.4336 - val_accuracy: 0.5889 - val_loss: 0.8558\n",
+      "Epoch 9/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 200ms/step - accuracy: 0.8411 - loss: 0.3744 - val_accuracy: 0.6166 - val_loss: 0.7971\n",
+      "Epoch 10/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 200ms/step - accuracy: 0.8227 - loss: 0.3752 - val_accuracy: 0.5949 - val_loss: 0.9897\n",
+      "Epoch 11/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 200ms/step - accuracy: 0.8595 - loss: 0.3430 - val_accuracy: 0.5949 - val_loss: 0.9049\n",
+      "Epoch 12/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 200ms/step - accuracy: 0.8467 - loss: 0.3634 - val_accuracy: 0.6146 - val_loss: 0.9294\n",
+      "Epoch 13/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 201ms/step - accuracy: 0.8505 - loss: 0.3547 - val_accuracy: 0.5949 - val_loss: 0.9743\n",
+      "Epoch 14/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 201ms/step - accuracy: 0.8548 - loss: 0.3412 - val_accuracy: 0.6028 - val_loss: 0.8529\n",
+      "Epoch 15/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 200ms/step - accuracy: 0.8503 - loss: 0.3535 - val_accuracy: 0.6126 - val_loss: 0.9585\n",
+      "Epoch 16/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 200ms/step - accuracy: 0.8791 - loss: 0.3164 - val_accuracy: 0.5968 - val_loss: 0.9744\n",
+      "Epoch 17/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 201ms/step - accuracy: 0.8262 - loss: 0.3774 - val_accuracy: 0.5593 - val_loss: 0.9227\n",
+      "Epoch 18/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 201ms/step - accuracy: 0.8661 - loss: 0.3071 - val_accuracy: 0.5474 - val_loss: 0.9052\n",
+      "Epoch 19/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 201ms/step - accuracy: 0.8599 - loss: 0.3151 - val_accuracy: 0.5751 - val_loss: 0.9794\n",
+      "Epoch 20/20\n",
+      "\u001b[1m152/152\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m31s\u001b[0m 202ms/step - accuracy: 0.8451 - loss: 0.3467 - val_accuracy: 0.5870 - val_loss: 0.9423\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<keras.src.callbacks.history.History at 0x7f91adcdd550>"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.fit(x=X_train, y=y_train, batch_size=10, epochs=20, validation_data=(X_test,y_test))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m16/16\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 16ms/step\n",
+      "Accuracy: 0.5869565217391305\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import accuracy_score\n",
+    "\n",
+    "y_pred = model.predict(X_test)\n",
+    "\n",
+    "y_predictions = []\n",
+    "for i in y_pred:\n",
+    "    y_predictions.append(round(i[0]))\n",
+    "\n",
+    "\n",
+    "accuracy = accuracy_score(y_pred=y_predictions, y_true=y_test)\n",
+    "\n",
+    "print(f\"Accuracy: {accuracy}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "y_predictions"
+   ]
+  }
+ ],
+ "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
+}
diff --git a/trickAIImageDetection/TrickImageDetection.ipynb b/trickAIImageDetection/TrickImageDetection.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 171,
+   "execution_count": 174,
    "metadata": {},
    "outputs": [],
    "source": [