{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" } }, "cells": [ { "cell_type": "markdown", "source": [ "**Changing directory to where D-Fire dataset is in drive**" ], "metadata": { "id": "Hepn8ZygcdXy" } }, { "cell_type": "code", "source": [ "%cd '/content/drive/MyDrive'" ], "metadata": { "id": "z8QR5O92pm8B", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "74008d90-9f77-46b2-ab40-94d6819b7a16" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/content/drive/MyDrive\n" ] } ] }, { "cell_type": "markdown", "source": [ "**Defining set of Augmentations**" ], "metadata": { "id": "WWuaIoH8ag00" } }, { "cell_type": "code", "source": [ "from PIL import Image, ImageEnhance, ImageFilter\n", "import os\n", "import random\n", "import shutil\n", "import numpy as np\n", "\n", "#Deine set of augmentations\n", "\n", "def adjust_brightness(image, factor):\n", " enhancer = ImageEnhance.Brightness(image)\n", " return enhancer.enhance(factor)\n", "\n", "def adjust_contrast(image, factor):\n", " enhancer = ImageEnhance.Contrast(image)\n", " return enhancer.enhance(factor)\n", "\n", "def add_noise(image):\n", " np_image = np.array(image)\n", " noise = np.random.normal(0, 0.1, np_image.shape).astype(np.uint8)\n", " noisy_image = Image.fromarray(np_image + noise)\n", " return noisy_image\n", "\n", "def color_jitter(image, factor=None):\n", " enhancer = ImageEnhance.Color(image)\n", " return enhancer.enhance(random.uniform(0.5, 1.5))\n", "\n", "def blur_image(image):\n", " return image.filter(ImageFilter.BLUR)\n", "\n", "#applying augmentation to images\n", "\n", "def apply_augmentations(image_path):\n", " image = Image.open(image_path)\n", " augmentations = [adjust_brightness, adjust_contrast, add_noise, color_jitter, blur_image]\n", " augmentation = random.choice(augmentations)\n", " if augmentation in [adjust_brightness, adjust_contrast, color_jitter]:\n", " factor = random.uniform(0.5, 1.5)\n", " image = augmentation(image, factor)\n", " else:\n", " image = augmentation(image)\n", " if image.mode == 'RGBA':\n", " image = image.convert('RGB')\n", " return image\n", "\n", "#copying annotations of the image to which augmentation is applied\n", "\n", "def copy_annotations(original_filename, new_filename, labels_dir):\n", " original_annotation_file = os.path.join(labels_dir, original_filename.replace('.jpg', '.txt'))\n", " new_annotation_file = os.path.join(labels_dir, new_filename.replace('.jpg', '.txt'))\n", " shutil.copyfile(original_annotation_file, new_annotation_file)\n", "\n", "#curating augmented dataset\n", "\n", "def augment_dataset(images_dir, labels_dir):\n", " for filename in os.listdir(images_dir):\n", " if filename.startswith(\"augmented_\"):\n", " continue\n", " if filename.endswith(\".jpg\") or filename.endswith(\".png\"):\n", " image_path = os.path.join(images_dir, filename)\n", " image = apply_augmentations(image_path)\n", " new_filename = \"augmented_\" + filename\n", " image.save(os.path.join(images_dir, new_filename))\n", " copy_annotations(filename, new_filename, labels_dir)\n", "\n", "\n" ], "metadata": { "id": "-WwEufbIMHXx" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "#storing augmented dataset to a new directory called D-Fire_Copy\n", "augment_dataset(\"/content/drive/MyDrive/D-Fire_copy/train/images\", \"/content/drive/MyDrive/D-Fire_copy/train/labels\")\n" ], "metadata": { "id": "sZy9xSKAHtel" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!pip install ultralytics" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "-_iVf3ihpdgH", "outputId": "c0ef687a-044f-4289-839a-edd3d99764ef" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: ultralytics in /usr/local/lib/python3.10/dist-packages (8.0.221)\n", "Requirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (3.7.1)\n", "Requirement already satisfied: numpy>=1.22.2 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (1.23.5)\n", "Requirement already satisfied: opencv-python>=4.6.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (4.8.0.76)\n", "Requirement already satisfied: pillow>=7.1.2 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (9.4.0)\n", "Requirement already satisfied: pyyaml>=5.3.1 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (6.0.1)\n", "Requirement already satisfied: requests>=2.23.0 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (2.31.0)\n", "Requirement already satisfied: scipy>=1.4.1 in /usr/local/lib/python3.10/dist-packages (from ultralytics) (1.11.3)\n", "Requirement already 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/usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (1.12)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (3.2.1)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (3.1.2)\n", "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (2023.6.0)\n", "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.8.0->ultralytics) (2.1.0)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.16.0)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.8.0->ultralytics) (2.1.3)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.8.0->ultralytics) (1.3.0)\n" ] } ] }, { "cell_type": "markdown", "source": [ "**Training the model**\n", "\n", "\n" ], "metadata": { "id": "BBltW-BJbea1" } }, { "cell_type": "code", "source": [ "from ultralytics import YOLO\n", "\n", "# Load a model\n", "model = YOLO('yolov8n.pt') # load an official model\n", "\n", "PROJECT = 'wildfire_augmented_final' # project name\n", "NAME = 'experiment_1' # run name\n", "\n", "model.train(\n", " data = '/content/drive/MyDrive/data_augmented.yaml',\n", " task = 'detect',\n", " epochs = 50,\n", " verbose = True,\n", " batch = 64,\n", " imgsz = 640,\n", " patience = 20,\n", " save = True,\n", " device = 0,\n", " workers = 2,\n", " project = PROJECT,\n", " name = NAME,\n", " cos_lr = True,\n", " lr0 = 0.01,\n", " lrf = 0.00001,\n", " warmup_epochs = 3,\n", " warmup_bias_lr = 0.000001,\n", " optimizer = 'Adam',\n", " seed = 42,\n", ")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "bC1ho1JnNxwu", "outputId": "f33460b2-cc18-419d-8209-e5fed8bcdddf" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Ultralytics YOLOv8.0.221 🚀 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n", "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=/content/drive/MyDrive/data_augmented.yaml, epochs=50, patience=20, batch=64, imgsz=640, save=True, save_period=-1, cache=False, device=0, workers=2, project=wildfire_augmented_final, name=experiment_113, exist_ok=False, pretrained=True, optimizer=Adam, verbose=True, seed=42, deterministic=True, single_cls=False, rect=False, cos_lr=True, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.0001, lrf=1e-05, momentum=0.937, weight_decay=0.0005, warmup_epochs=3, warmup_momentum=0.8, warmup_bias_lr=1e-06, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, tracker=botsort.yaml, save_dir=wildfire_augmented_final/experiment_113\n", "Overriding model.yaml nc=80 with nc=2\n", "\n", " from n params module arguments \n", " 0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2] \n", " 1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2] \n", " 2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True] \n", " 3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] \n", " 4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True] \n", " 5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] \n", " 6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] \n", " 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] \n", " 8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True] \n", " 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] \n", " 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n", " 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", " 12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] \n", " 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n", " 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", " 15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1] \n", " 16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] \n", " 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", " 18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1] \n", " 19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] \n", " 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n", " 21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] \n", " 22 [15, 18, 21] 1 751702 ultralytics.nn.modules.head.Detect [2, [64, 128, 256]] \n", "Model summary: 225 layers, 3011238 parameters, 3011222 gradients, 8.2 GFLOPs\n", "\n", "Transferred 319/355 items from pretrained weights\n", "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir wildfire_augmented_final/experiment_113', view at http://localhost:6006/\n", "Freezing layer 'model.22.dfl.conv.weight'\n", "\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks with YOLOv8n...\n", "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/drive/MyDrive/D-Fire_copy/train/labels.cache... 27900 images, 12706 backgrounds, 0 corrupt: 100%|██████████| 27900/27900 [00:00\n", "curves: ['Precision-Recall(B)', 'F1-Confidence(B)', 'Precision-Confidence(B)', 'Recall-Confidence(B)']\n", "curves_results: [[array([ 0, 0.001001, 0.002002, 0.003003, 0.004004, 0.005005, 0.006006, 0.007007, 0.008008, 0.009009, 0.01001, 0.011011, 0.012012, 0.013013, 0.014014, 0.015015, 0.016016, 0.017017, 0.018018, 0.019019, 0.02002, 0.021021, 0.022022, 0.023023,\n", " 0.024024, 0.025025, 0.026026, 0.027027, 0.028028, 0.029029, 0.03003, 0.031031, 0.032032, 0.033033, 0.034034, 0.035035, 0.036036, 0.037037, 0.038038, 0.039039, 0.04004, 0.041041, 0.042042, 0.043043, 0.044044, 0.045045, 0.046046, 0.047047,\n", " 0.048048, 0.049049, 0.05005, 0.051051, 0.052052, 0.053053, 0.054054, 0.055055, 0.056056, 0.057057, 0.058058, 0.059059, 0.06006, 0.061061, 0.062062, 0.063063, 0.064064, 0.065065, 0.066066, 0.067067, 0.068068, 0.069069, 0.07007, 0.071071,\n", " 0.072072, 0.073073, 0.074074, 0.075075, 0.076076, 0.077077, 0.078078, 0.079079, 0.08008, 0.081081, 0.082082, 0.083083, 0.084084, 0.085085, 0.086086, 0.087087, 0.088088, 0.089089, 0.09009, 0.091091, 0.092092, 0.093093, 0.094094, 0.095095,\n", " 0.096096, 0.097097, 0.098098, 0.099099, 0.1001, 0.1011, 0.1021, 0.1031, 0.1041, 0.10511, 0.10611, 0.10711, 0.10811, 0.10911, 0.11011, 0.11111, 0.11211, 0.11311, 0.11411, 0.11512, 0.11612, 0.11712, 0.11812, 0.11912,\n", " 0.12012, 0.12112, 0.12212, 0.12312, 0.12412, 0.12513, 0.12613, 0.12713, 0.12813, 0.12913, 0.13013, 0.13113, 0.13213, 0.13313, 0.13413, 0.13514, 0.13614, 0.13714, 0.13814, 0.13914, 0.14014, 0.14114, 0.14214, 0.14314,\n", " 0.14414, 0.14515, 0.14615, 0.14715, 0.14815, 0.14915, 0.15015, 0.15115, 0.15215, 0.15315, 0.15415, 0.15516, 0.15616, 0.15716, 0.15816, 0.15916, 0.16016, 0.16116, 0.16216, 0.16316, 0.16416, 0.16517, 0.16617, 0.16717,\n", " 0.16817, 0.16917, 0.17017, 0.17117, 0.17217, 0.17317, 0.17417, 0.17518, 0.17618, 0.17718, 0.17818, 0.17918, 0.18018, 0.18118, 0.18218, 0.18318, 0.18418, 0.18519, 0.18619, 0.18719, 0.18819, 0.18919, 0.19019, 0.19119,\n", " 0.19219, 0.19319, 0.19419, 0.1952, 0.1962, 0.1972, 0.1982, 0.1992, 0.2002, 0.2012, 0.2022, 0.2032, 0.2042, 0.20521, 0.20621, 0.20721, 0.20821, 0.20921, 0.21021, 0.21121, 0.21221, 0.21321, 0.21421, 0.21522,\n", " 0.21622, 0.21722, 0.21822, 0.21922, 0.22022, 0.22122, 0.22222, 0.22322, 0.22422, 0.22523, 0.22623, 0.22723, 0.22823, 0.22923, 0.23023, 0.23123, 0.23223, 0.23323, 0.23423, 0.23524, 0.23624, 0.23724, 0.23824, 0.23924,\n", " 0.24024, 0.24124, 0.24224, 0.24324, 0.24424, 0.24525, 0.24625, 0.24725, 0.24825, 0.24925, 0.25025, 0.25125, 0.25225, 0.25325, 0.25425, 0.25526, 0.25626, 0.25726, 0.25826, 0.25926, 0.26026, 0.26126, 0.26226, 0.26326,\n", " 0.26426, 0.26527, 0.26627, 0.26727, 0.26827, 0.26927, 0.27027, 0.27127, 0.27227, 0.27327, 0.27427, 0.27528, 0.27628, 0.27728, 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0.91491, 0.91592, 0.91692, 0.91792, 0.91892, 0.91992, 0.92092, 0.92192, 0.92292, 0.92392, 0.92492, 0.92593, 0.92693, 0.92793, 0.92893, 0.92993, 0.93093, 0.93193, 0.93293, 0.93393, 0.93493, 0.93594,\n", " 0.93694, 0.93794, 0.93894, 0.93994, 0.94094, 0.94194, 0.94294, 0.94394, 0.94494, 0.94595, 0.94695, 0.94795, 0.94895, 0.94995, 0.95095, 0.95195, 0.95295, 0.95395, 0.95495, 0.95596, 0.95696, 0.95796, 0.95896, 0.95996,\n", " 0.96096, 0.96196, 0.96296, 0.96396, 0.96496, 0.96597, 0.96697, 0.96797, 0.96897, 0.96997, 0.97097, 0.97197, 0.97297, 0.97397, 0.97497, 0.97598, 0.97698, 0.97798, 0.97898, 0.97998, 0.98098, 0.98198, 0.98298, 0.98398,\n", " 0.98498, 0.98599, 0.98699, 0.98799, 0.98899, 0.98999, 0.99099, 0.99199, 0.99299, 0.99399, 0.99499, 0.996, 0.997, 0.998, 0.999, 1]), array([[ 0.94536, 0.94536, 0.93661, ..., 0, 0, 0],\n", " [ 0.9211, 0.9211, 0.91389, ..., 0, 0, 0]]), 'Confidence', 'Recall']]\n", "fitness: 0.48055197953338624\n", "keys: ['metrics/precision(B)', 'metrics/recall(B)', 'metrics/mAP50(B)', 'metrics/mAP50-95(B)']\n", "maps: array([ 0.52652, 0.3718])\n", "names: {0: 'smoke', 1: 'fire'}\n", "plot: True\n", "results_dict: {'metrics/precision(B)': 0.7782241351423715, 'metrics/recall(B)': 0.7010638245453247, 'metrics/mAP50(B)': 0.7630915378176291, 'metrics/mAP50-95(B)': 0.44915869527958147, 'fitness': 0.48055197953338624}\n", "save_dir: PosixPath('wildfire_augmented_final/experiment_113')\n", "speed: {'preprocess': 0.15709546683068598, 'inference': 1.5296065745387228, 'loss': 0.0002943241279156556, 'postprocess': 1.9978822389169413}\n", "task: 'detect'" ] }, "metadata": {}, "execution_count": 6 } ] }, { "cell_type": "markdown", "source": [ "**Testing the model**" ], "metadata": { "id": "6HlU8fTNbmfe" } }, { "cell_type": "code", "source": [ "from ultralytics import YOLO\n", "\n", "model = YOLO('/content/drive/MyDrive/wildfire_augmented_final/experiment_113/weights/best.pt')\n", "\n", "model.val(split='test', batch=48, imgsz=640, verbose=True, conf = 0.1, iou = 0.5)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "3KeuX7g4xekC", "outputId": "0dd7b33d-9e9f-455a-9e57-978c6e587b43" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Ultralytics YOLOv8.0.221 🚀 Python-3.10.12 torch-2.1.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n", "Model summary (fused): 168 layers, 3006038 parameters, 0 gradients, 8.1 GFLOPs\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/drive/MyDrive/D-Fire_copy/test/labels... 4306 images, 2005 backgrounds, 8 corrupt: 100%|██████████| 4306/4306 [52:17<00:00, 1.37it/s]" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB10769.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0297]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB10770.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0078]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB10775.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0156]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB10821.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0094]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB11090.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0028]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB11598.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0359]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB11600.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0562]\n", "\u001b[34m\u001b[1mval: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/D-Fire_copy/test/images/WEB11606.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0028]\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/drive/MyDrive/D-Fire_copy/test/labels.cache\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ " Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 90/90 [05:23<00:00, 3.60s/it]\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ " all 4298 5176 0.778 0.723 0.783 0.479\n", " smoke 4298 2307 0.836 0.791 0.843 0.557\n", " fire 4298 2869 0.721 0.656 0.723 0.401\n", "Speed: 0.2ms preprocess, 2.9ms inference, 0.0ms loss, 0.7ms postprocess per image\n", "Results saved to \u001b[1mruns/detect/val4\u001b[0m\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "ultralytics.utils.metrics.DetMetrics object with attributes:\n", "\n", "ap_class_index: array([0, 1])\n", "box: ultralytics.utils.metrics.Metric object\n", "confusion_matrix: \n", "curves: ['Precision-Recall(B)', 'F1-Confidence(B)', 'Precision-Confidence(B)', 'Recall-Confidence(B)']\n", "curves_results: [[array([ 0, 0.001001, 0.002002, 0.003003, 0.004004, 0.005005, 0.006006, 0.007007, 0.008008, 0.009009, 0.01001, 0.011011, 0.012012, 0.013013, 0.014014, 0.015015, 0.016016, 0.017017, 0.018018, 0.019019, 0.02002, 0.021021, 0.022022, 0.023023,\n", " 0.024024, 0.025025, 0.026026, 0.027027, 0.028028, 0.029029, 0.03003, 0.031031, 0.032032, 0.033033, 0.034034, 0.035035, 0.036036, 0.037037, 0.038038, 0.039039, 0.04004, 0.041041, 0.042042, 0.043043, 0.044044, 0.045045, 0.046046, 0.047047,\n", " 0.048048, 0.049049, 0.05005, 0.051051, 0.052052, 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0.9039, 0.9049, 0.90591, 0.90691, 0.90791, 0.90891, 0.90991, 0.91091, 0.91191,\n", " 0.91291, 0.91391, 0.91491, 0.91592, 0.91692, 0.91792, 0.91892, 0.91992, 0.92092, 0.92192, 0.92292, 0.92392, 0.92492, 0.92593, 0.92693, 0.92793, 0.92893, 0.92993, 0.93093, 0.93193, 0.93293, 0.93393, 0.93493, 0.93594,\n", " 0.93694, 0.93794, 0.93894, 0.93994, 0.94094, 0.94194, 0.94294, 0.94394, 0.94494, 0.94595, 0.94695, 0.94795, 0.94895, 0.94995, 0.95095, 0.95195, 0.95295, 0.95395, 0.95495, 0.95596, 0.95696, 0.95796, 0.95896, 0.95996,\n", " 0.96096, 0.96196, 0.96296, 0.96396, 0.96496, 0.96597, 0.96697, 0.96797, 0.96897, 0.96997, 0.97097, 0.97197, 0.97297, 0.97397, 0.97497, 0.97598, 0.97698, 0.97798, 0.97898, 0.97998, 0.98098, 0.98198, 0.98298, 0.98398,\n", " 0.98498, 0.98599, 0.98699, 0.98799, 0.98899, 0.98999, 0.99099, 0.99199, 0.99299, 0.99399, 0.99499, 0.996, 0.997, 0.998, 0.999, 1]), array([[ 0.83788, 0.83788, 0.83788, ..., 0, 0, 0],\n", " [ 0.77344, 0.77344, 0.77344, ..., 0, 0, 0]]), 'Confidence', 'Recall']]\n", "fitness: 0.5091951640809799\n", "keys: ['metrics/precision(B)', 'metrics/recall(B)', 'metrics/mAP50(B)', 'metrics/mAP50-95(B)']\n", "maps: array([ 0.55675, 0.40081])\n", "names: {0: 'smoke', 1: 'fire'}\n", "plot: True\n", "results_dict: {'metrics/precision(B)': 0.7784017040413911, 'metrics/recall(B)': 0.7231331651150974, 'metrics/mAP50(B)': 0.7829476456778637, 'metrics/mAP50-95(B)': 0.47877822168132605, 'fitness': 0.5091951640809799}\n", "save_dir: PosixPath('runs/detect/val4')\n", "speed: {'preprocess': 0.17816114004072114, 'inference': 2.883997669104589, 'loss': 0.0004631355786223698, 'postprocess': 0.6578453422535736}\n", "task: 'detect'" ] }, "metadata": {}, "execution_count": 7 } ] }, { "cell_type": "markdown", "source": [ "Deploying APP on Huggingface" ], "metadata": { "id": "1iCOEPiHD1Xp" } }, { "cell_type": "code", "source": [ "#installing required dependencies\n", "\n", "!pip install huggingface_hub\n", "!apt-get install git-lfs" ], "metadata": { "id": "qjnPHFtuqEVU", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "b295e04e-6d0c-4ade-bb6c-a9371121b34f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (0.19.4)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (3.13.1)\n", "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2023.6.0)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2.31.0)\n", "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.66.1)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (6.0.1)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.5.0)\n", "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (23.2)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.3.2)\n", "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.6)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2.0.7)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2023.11.17)\n", "Reading package lists... Done\n", "Building dependency tree... Done\n", "Reading state information... Done\n", "git-lfs is already the newest version (3.0.2-1ubuntu0.2).\n", "0 upgraded, 0 newly installed, 0 to remove and 15 not upgraded.\n" ] } ] }, { "cell_type": "code", "source": [ "#cloning to Hugging Face Project repository\n", "!git clone https://huggingface.co/spaces/ankitkupadhyay/fire_and_smoke" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "jTWpvkqaD_6q", "outputId": "dac7d757-6b9a-4b8e-b3a5-05c0bae27f2a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Cloning into 'fire_and_smoke'...\n", "remote: Enumerating objects: 4, done.\u001b[K\n", "remote: Total 4 (delta 0), reused 0 (delta 0), pack-reused 4\u001b[K\n", "Unpacking objects: 100% (4/4), 664 bytes | 12.00 KiB/s, done.\n" ] } ] }, { "cell_type": "markdown", "source": [ "**Copying the streamlit application file (app.py), best weights from the experiment(best.pt) and requirements text (requirements.txt) to the repository**" ], "metadata": { "id": "HbyKTDUrcBzR" } }, { "cell_type": "code", "source": [ "!cp /content/drive/MyDrive/app.py /content/drive/MyDrive/fire_and_smoke" ], "metadata": { "id": "xW-qWBYOEIcg" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!cp /content/drive/MyDrive/wildfire_augmented_final/experiment_113/weights/best.pt /content/drive/MyDrive/fire_and_smoke" ], "metadata": { "id": "KPVxykaOE37G" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!cp /content/drive/MyDrive/requirements.txt /content/drive/MyDrive/fire_and_smoke" ], "metadata": { "id": "nhYvNIkVFHT6" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "#pushing changes to repository\n", "\n", "%cd /content/drive/MyDrive/fire_and_smoke\n", "!git config --global user.email \"ankitkupadhyay1202@gmail.com\"\n", "!git config --global user.name \"AnkitKUpadhyay\"\n", "!chmod +x .git/hooks/post-commit\n", "!chmod +x .git/hooks/pre-push\n", "!git add .\n", "!git commit -m \"Adding app file, requirements text, and model weights\"\n", "!git push https://ankitkupadhyay: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@huggingface.co/spaces/ankitkupadhyay/fire_and_smoke" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ZpqECTYaGWAA", "outputId": "551bf010-ebee-4198-8e12-5e7a140fdc1f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/content/drive/MyDrive/fire_and_smoke\n", "On branch main\n", "Your branch is ahead of 'origin/main' by 1 commit.\n", " (use \"git push\" to publish your local commits)\n", "\n", "nothing to commit, working tree clean\n", "Uploading LFS objects: 100% (1/1), 6.2 MB | 0 B/s, done.\n", "Enumerating objects: 6, done.\n", "Counting objects: 100% (6/6), done.\n", "Delta compression using up to 2 threads\n", "Compressing objects: 100% (5/5), done.\n", "Writing objects: 100% (5/5), 1.77 KiB | 302.00 KiB/s, done.\n", "Total 5 (delta 0), reused 0 (delta 0), pack-reused 0\n", "To https://huggingface.co/spaces/ankitkupadhyay/fire_and_smoke\n", " 561583f..9b5c19b main -> main\n" ] } ] } ] }