diff --git "a/Appendix - Export Pytorch to ONNX.ipynb" "b/Appendix - Export Pytorch to ONNX.ipynb" new file mode 100644--- /dev/null +++ "b/Appendix - Export Pytorch to ONNX.ipynb" @@ -0,0 +1,602 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "14e5773e-03cc-4794-aa48-16957a373968", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "from PIL import Image\n", + "import torch.nn as nn\n", + "import torchvision.models as models\n", + "from torchvision import transforms\n", + "from matplotlib import pyplot as plt # Ensure this is imported at the top" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "id": "3120036f-bbb0-4723-a794-628e546589f5", + "metadata": {}, + "outputs": [], + "source": [ + "def generate_classification_report(df, label_col='label', pred_col='prediction'):\n", + " y_true = df[label_col]\n", + " y_pred = df[pred_col]\n", + "\n", + " # 1. Classification report\n", + " print(\"\\nšŸ“Š Classification Report:\")\n", + " report = classification_report(y_true, y_pred, output_dict=True)\n", + " report_df = pd.DataFrame(report).transpose()\n", + " print(report_df)\n", + "\n", + " # 2. Confusion matrix\n", + " print(\"\\nšŸ” Confusion Matrix:\")\n", + " cm = confusion_matrix(y_true, y_pred)\n", + " labels = sorted(set(y_true) | set(y_pred))\n", + " cm_df = pd.DataFrame(cm, index=labels, columns=labels)\n", + " print(cm_df)\n", + "\n", + " # 3. Plot the confusion matrix\n", + " plt.figure(figsize=(8, 6))\n", + " sns.heatmap(cm_df, annot=True, fmt=\"d\", cmap=\"Blues\")\n", + " plt.xlabel(\"Predicted\")\n", + " plt.ylabel(\"Actual\")\n", + " plt.title(\"Confusion Matrix\")\n", + " plt.show()\n", + "\n", + " # 4. Explanation of metrics\n", + " print(\"\\nšŸ“˜ Metric Explanations:\")\n", + " print(\"• Precision: Among all predicted as class X, how many are actually class X?\")\n", + " print(\"• Recall: Among all actual class X, how many were correctly predicted?\")\n", + " print(\"• F1-score: Harmonic mean of precision and recall (balance between both).\")\n", + " print(\"• Support: Number of true instances of each class in the dataset.\")\n", + "\n", + " return report_df, cm_df\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "9362877b-185b-409e-9bb0-4fddc4b64e68", + "metadata": {}, + "outputs": [], + "source": [ + "class ResNetEmbeddingModel(nn.Module):\n", + "\tdef __init__(self, resnet_version='ResNet18'):\n", + "\t\tsuper(ResNetEmbeddingModel, self).__init__()\n", + "\t\t\n", + "\t\t# Choose ResNet version\n", + "\t\tif resnet_version == 'ResNet18':\n", + "\t\t\tself.backbone = models.resnet18(weights=None) # No internet download\n", + "\t\telif resnet_version == 'ResNet34':\n", + "\t\t\tself.backbone = models.resnet34(weights=None)\n", + "\t\telse:\n", + "\t\t\traise ValueError(\"Unsupported ResNet version\")\n", + "\n", + "\t\t# Remove final FC layer\n", + "\t\tself.backbone = nn.Sequential(*list(self.backbone.children())[:-1])\n", + "\n", + "\tdef forward(self, x):\n", + "\t\treturn self.backbone(x).squeeze()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "37e43dbe-bf17-43a2-9d9b-319d19ec22bd", + "metadata": {}, + "outputs": [], + "source": [ + "class Predictor:\n", + "\t\"\"\"\n", + "\tPredictor class for computing similarity between two images using a ResNet embedding model.\n", + "\t\n", + "\tArgs:\n", + "\t\tresnet_version (str): Version of ResNet backbone to use ('ResNet18' or 'ResNet34').\n", + "\t\tpretrained (bool): Whether to use pretrained weights (currently unused in your model).\n", + "\t\tlocal_weight (str or None): Path to local checkpoint weights.\n", + "\t\tdevice (str): Device to run the model on ('cpu' or 'cuda').\n", + "\t\"\"\"\n", + "\t\n", + "\tdef __init__(self, resnet_version='ResNet18', local_weight=None, distance_threshold=None, device=\"cpu\"):\n", + "\t\t# Initialize the embedding model with specified parameters\n", + "\t\t\n", + "\t\tself.model = ResNetEmbeddingModel(resnet_version=resnet_version)\n", + "\t\tself.distance_threshold = distance_threshold\n", + "\t\tself.device = device\n", + "\t\t# Define preprocessing transforms to match model input requirements\n", + "\t\tself.transform = transforms.Compose([\n", + "\t\t\ttransforms.Resize((224, 224)), # Resize to model input size\n", + "\t\t\ttransforms.ToTensor(),\t\t # Convert PIL image to tensor\n", + "\t\t\ttransforms.Normalize(\t\t\t# Normalize with ImageNet stats\n", + "\t\t\t\tmean=[0.485, 0.456, 0.406], \n", + "\t\t\t\tstd=[0.229, 0.224, 0.225]\n", + "\t\t\t)\n", + "\t\t])\n", + "\n", + "\n", + "\t\t#Loading weights\n", + "\t\tcheckpoint = torch.load(local_weight, map_location=self.device, weights_only=False)\t \n", + "\t\tself.model.load_state_dict(checkpoint['model_state_dict'])\n", + "\t\tself.model.to(device)\n", + "\t\tself.model.eval()\n", + "\n", + "\t # Get threshold if not provided\n", + "\t\tif distance_threshold is None:\n", + "\t\t\tself.distance_threshold = checkpoint.get('distance_threshold', 1.0)\n", + "\t\t\tprint(f\"Using trained distance threshold: {self.distance_threshold:.4f}\")\n", + "\t \n", + "\t\n", + "\tdef compute_distance(self, embedding1: torch.Tensor, embedding2: torch.Tensor) -> torch.Tensor:\n", + "\t\t\"\"\"\n", + "\t\tCompute the pairwise distance between two embeddings.\n", + "\t\t\n", + "\t\tArgs:\n", + "\t\t\tembedding1 (torch.Tensor): Embedding tensor of first image.\n", + "\t\t\tembedding2 (torch.Tensor): Embedding tensor of second image.\n", + "\t\t\n", + "\t\tReturns:\n", + "\t\t\ttorch.Tensor: The pairwise distance between embeddings.\n", + "\t\t\"\"\"\n", + "\t\treturn torch.nn.functional.pairwise_distance(embedding1, embedding2, p=2).item()\n", + "\n", + "\t# Load and process images\n", + "\tdef load_image(self, path):\n", + "\t\traw_img = Image.open(path).convert('RGB')\n", + "\t\treturn raw_img, self.transform(raw_img).unsqueeze(0).to(device)\n", + "\n", + "\t\n", + "\tdef get_similarity(self, genuine_img_path: str, doubted_img_path: str, display_images: bool = False) -> torch.Tensor:\n", + "\t\t\"\"\"\n", + "\t\tCalculate similarity (distance) between two images based on their embeddings.\n", + "\t\n", + "\t\tArgs:\n", + "\t\t\tgenuine_img_path (str): File path to the genuine image.\n", + "\t\t\tdoubted_img_path (str): File path to the doubted image.\n", + "\t\t\tdisplay_images (bool): If True, display the two images side by side with titles.\n", + "\t\n", + "\t\tReturns:\n", + "\t\t\ttorch.Tensor: The distance score between the two image embeddings.\n", + "\t\t\"\"\"\n", + "\t\t# Load images and convert to RGB\n", + "\t\timg1, img1_tensor = self.load_image(genuine_img_path)\n", + "\t\timg2, img2_tensor = self.load_image(doubted_img_path)\n", + "\t\t\n", + "\t\t# Pass through model to get embeddings\n", + "\t\twith torch.no_grad():\n", + "\t\t\temb1 = self.model(img1_tensor)\n", + "\t\t\temb2 = self.model(img2_tensor)\n", + "\t\t\n", + "\t\t# Compute similarity (distance)\n", + "\t\tdistance = self.compute_distance(emb1, emb2)\n", + "\t\t\t\n", + "\t\t# Determine if genuine (same person)\n", + "\t\tis_genuine = distance < self.distance_threshold\n", + "\t\n", + "\t\t# Optionally display images with titles and similarity score\n", + "\t\tif display_images:\n", + "\t\t\tplt.figure(figsize=(8, 4))\n", + "\t\t\tplt.suptitle(f\"Similarity (Distance): {distance:.4f} - Label Genuine {is_genuine}\", fontsize=14)\n", + "\t\t\tplt.subplot(1, 2, 1)\n", + "\t\t\tplt.title(\"Genuine\")\n", + "\t\t\tplt.axis(\"off\")\n", + "\t\t\tplt.imshow(img1)\n", + "\t\t\tplt.subplot(1, 2, 2)\n", + "\t\t\tplt.title(\"Doubted\")\n", + "\t\t\tplt.axis(\"off\")\n", + "\t\t\tplt.imshow(img2)\n", + "\t\t\tplt.show()\n", + "\t\t \n", + "\t\t \n", + "\t\treturn is_genuine, distance\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "1bf5422f-5f43-4b7a-aacf-eed3ad525fd2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using device: cuda\n", + "Using trained distance threshold: 5.0859\n" + ] + } + ], + "source": [ + "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", + "print(f\"Using device: {device}\")\n", + "\n", + "\n", + "model_name = \"ResNet34\"\n", + "local_weights_path = \"../../model/models_checkpoints/resnet-34-v1/best_model.pth\"\n", + "# Initialize model with local weights\n", + "predictor = Predictor(\n", + "\tresnet_version=model_name,\n", + "\tlocal_weight=local_weights_path,\n", + "\tdevice= device\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "e56c7424-265a-46f0-872d-25252dc4cde0", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import random\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 177, + "id": "80f7bf25-7ae8-4a9d-8541-18455740f3f3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "img_genuine_path : 0fa39728-2196-4311-8575-fe3aee2266a6.png\n", + "img_doubted_path : 79986c97-72e1-4bf1-976c-1d9937875e14.png\n", + "label : 0\n", + "\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "(False, 6.852903842926025)" + ] + }, + "execution_count": 177, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "folder_images = \"../../data/classify/preprared_data/images/\"\n", + "cpt = random.randint(0, len(df_test)-1)\n", + "row = df_test.values[cpt]\n", + "\n", + "img_genuine_path = row[0]\n", + "img_doubted_path = row[1]\n", + "label = row[2]\n", + "print(f\"\"\"img_genuine_path : {img_genuine_path}\n", + "img_doubted_path : {img_doubted_path}\n", + "label : {label}\n", + "\"\"\")\n", + "predictor.get_similarity(os.path.join(folder_images,img_genuine_path),\n", + "\t\t\t\t\t\tos.path.join(folder_images,img_doubted_path),\n", + "\t\t\t\t\t\t display_images=True\n", + "\t\t\t\t\t\t)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "b6b10c32-4947-4a7d-b743-aff75a999a96", + "metadata": {}, + "outputs": [], + "source": [ + "df_test = pd.read_excel(\"../../data/classify/preprared_data/labels/test_pairs.xlsx\")" + ] + }, + { + "cell_type": "code", + "execution_count": 178, + "id": "e284b498-d48d-446b-a9fe-89bff3bf44e1", + "metadata": {}, + "outputs": [], + "source": [ + "df_test[\"prediction\"] = [predictor.get_similarity(os.path.join(folder_images,row[0]),\n", + "\t\t\t\t\t\tos.path.join(folder_images,row[1]),\n", + "\t\t\t\t\t\t display_images=False\n", + "\t\t\t\t\t\t)[0] for row in df_test.values]" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "id": "4a2dd7e7-c88b-486b-bec4-7cb1cd40e710", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.metrics import classification_report, confusion_matrix\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "id": "45b0d3d0-59a6-4cd4-8b4b-683734a5aa6e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "šŸ“Š Classification Report:\n", + " precision recall f1-score support\n", + "0 0.901954 0.804429 0.850405 6141.000000\n", + "1 0.664056 0.815527 0.732038 2911.000000\n", + "accuracy 0.807998 0.807998 0.807998 0.807998\n", + "macro avg 0.783005 0.809978 0.791221 9052.000000\n", + "weighted avg 0.825449 0.807998 0.812340 9052.000000\n", + "\n", + "šŸ” Confusion Matrix:\n", + " 0 1\n", + "0 4940 1201\n", + "1 537 2374\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "šŸ“˜ Metric Explanations:\n", + "• Precision: Among all predicted as class X, how many are actually class X?\n", + "• Recall: Among all actual class X, how many were correctly predicted?\n", + "• F1-score: Harmonic mean of precision and recall (balance between both).\n", + "• Support: Number of true instances of each class in the dataset.\n" + ] + }, + { + "data": { + "text/plain": [ + "( precision recall f1-score support\n", + " 0 0.901954 0.804429 0.850405 6141.000000\n", + " 1 0.664056 0.815527 0.732038 2911.000000\n", + " accuracy 0.807998 0.807998 0.807998 0.807998\n", + " macro avg 0.783005 0.809978 0.791221 9052.000000\n", + " weighted avg 0.825449 0.807998 0.812340 9052.000000,\n", + " 0 1\n", + " 0 4940 1201\n", + " 1 537 2374)" + ] + }, + "execution_count": 184, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "generate_classification_report(df_test, label_col='label', pred_col='prediction')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3dbcf631-eaf5-4257-b539-ef94bab05f5f", + "metadata": {}, + "outputs": [], + "source": [ + "df_test[\"prediction\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2dc880b6-bf68-4069-a216-695d453172cc", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 142, + "id": "d8ef41f2-a312-4f6c-9414-491cc9bbf695", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'75c1ef1b-a2c3-404d-9578-3d476d7203e2.png'" + ] + }, + "execution_count": 142, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "img_doubted_path" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "dd4cd5fd-9cb1-4c46-8dc9-4720cee6c7d1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
image_1_pathimage_2_pathlabel
0fe8df58a-3e19-44c2-899f-f2fa299e20ac.pngafdb369c-1d37-4f50-8975-3056a804ac83.png1
1fe8df58a-3e19-44c2-899f-f2fa299e20ac.pngf654e9c3-bca8-4ddf-b3a4-c5b9ce9a0391.png1
2fe8df58a-3e19-44c2-899f-f2fa299e20ac.png3ab7166b-d310-4add-abfc-f81ac655e655.png1
3fe8df58a-3e19-44c2-899f-f2fa299e20ac.png90289116-d20b-4549-b427-cd93ec5b7934.png1
4fe8df58a-3e19-44c2-899f-f2fa299e20ac.png88d13350-e120-461b-be76-38e3b640961e.png1
............
13568e2a19373-80be-4299-b1f8-2a956805b65e.png8ac8da82-1651-4d60-a2c9-92129cd9cba0.png0
13569e2a19373-80be-4299-b1f8-2a956805b65e.pnga3036049-b79b-4be9-9ec3-5117366f27c1.png0
13570e2a19373-80be-4299-b1f8-2a956805b65e.pngbfb0f988-df5f-4ab8-9953-7f0a20d67eb3.png0
13571e2a19373-80be-4299-b1f8-2a956805b65e.png628655f4-c3e0-4619-b677-0e4c2f2dff36.png0
13572e2a19373-80be-4299-b1f8-2a956805b65e.pngc5000d04-3996-4c72-a833-d73f358e04c8.png0
\n", + "

13573 rows Ɨ 3 columns

\n", + "
" + ], + "text/plain": [ + " image_1_path \\\n", + "0 fe8df58a-3e19-44c2-899f-f2fa299e20ac.png \n", + "1 fe8df58a-3e19-44c2-899f-f2fa299e20ac.png \n", + "2 fe8df58a-3e19-44c2-899f-f2fa299e20ac.png \n", + "3 fe8df58a-3e19-44c2-899f-f2fa299e20ac.png \n", + "4 fe8df58a-3e19-44c2-899f-f2fa299e20ac.png \n", + "... ... \n", + "13568 e2a19373-80be-4299-b1f8-2a956805b65e.png \n", + "13569 e2a19373-80be-4299-b1f8-2a956805b65e.png \n", + "13570 e2a19373-80be-4299-b1f8-2a956805b65e.png \n", + "13571 e2a19373-80be-4299-b1f8-2a956805b65e.png \n", + "13572 e2a19373-80be-4299-b1f8-2a956805b65e.png \n", + "\n", + " image_2_path label \n", + "0 afdb369c-1d37-4f50-8975-3056a804ac83.png 1 \n", + "1 f654e9c3-bca8-4ddf-b3a4-c5b9ce9a0391.png 1 \n", + "2 3ab7166b-d310-4add-abfc-f81ac655e655.png 1 \n", + "3 90289116-d20b-4549-b427-cd93ec5b7934.png 1 \n", + "4 88d13350-e120-461b-be76-38e3b640961e.png 1 \n", + "... ... ... \n", + "13568 8ac8da82-1651-4d60-a2c9-92129cd9cba0.png 0 \n", + "13569 a3036049-b79b-4be9-9ec3-5117366f27c1.png 0 \n", + "13570 bfb0f988-df5f-4ab8-9953-7f0a20d67eb3.png 0 \n", + "13571 628655f4-c3e0-4619-b677-0e4c2f2dff36.png 0 \n", + "13572 c5000d04-3996-4c72-a833-d73f358e04c8.png 0 \n", + "\n", + "[13573 rows x 3 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_test" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}