AbdullahImran/DeepLearningProject
Deep Learning Project Dataset Summary This repository contains the datasets, trained models, notebooks, experiments, feature-extraction outputs, and supporting resources developed for a deep learning project focused on fire detection, fire severity classification, and related computer vision tasks. The project covers multiple stages of a deep learning workflow, including binary fire classification, three-class fire severity classification, feature extraction… See the full description on the dataset page: https://huggingface.co/datasets/AbdullahImran/DeepLearningProject.
0569
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25 "name": "stdout",
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27 "text": [
28 "Mounted at /content/drive\n"
29 ]
30 }
31 ],
32 "source": [
33 "from google.colab import drive\n",
34 "drive.mount('/content/drive')"
35 ]
36 },
37 {
38 "cell_type": "markdown",
39 "metadata": {},
40 "source": [
41 "# DL Project File 3: Handling Class Imbalance for Severity Dataset via Diffusion Model 2"
42 ]
43 },
44 {
45 "cell_type": "code",
46 "execution_count": 2,
47 "metadata": {
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50 "status": "ok",
51 "timestamp": 1736782392046,
52 "user": {
53 "displayName": "Maham Ahmad",
54 "userId": "04446938859370329711"
55 },
56 "user_tz": -300
57 },
58 "id": "YoNCs_-DSoZ6"
59 },
60 "outputs": [],
61 "source": [
62 "from huggingface_hub import login\n",
63 "\n",
64 "# Replace with your Hugging Face token\n",
65 "login(token=\"nice_token\")"
66 ]
67 },
68 {
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254 "executionInfo": {
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257 "timestamp": 1736782812957,
258 "user": {
259 "displayName": "Maham Ahmad",
260 "userId": "04446938859370329711"
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264 "id": "vyvkT4a4TCFI",
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268 {
269 "name": "stderr",
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271 "text": [
272 "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
273 ]
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283 "0it [00:00, ?it/s]"
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293 "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
294 "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
295 "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
296 "You will be able to reuse this secret in all of your notebooks.\n",
297 "Please note that authentication is recommended but still optional to access public models or datasets.\n",
298 " warnings.warn(\n"
299 ]
300 },
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504 "text/plain": [
505 "Loading pipeline components...: 0%| | 0/6 [00:00<?, ?it/s]"
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508 "metadata": {},
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511 {
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514 "StableDiffusionPipeline {\n",
515 " \"_class_name\": \"StableDiffusionPipeline\",\n",
516 " \"_diffusers_version\": \"0.32.1\",\n",
517 " \"_name_or_path\": \"stabilityai/stable-diffusion-2\",\n",
518 " \"feature_extractor\": [\n",
519 " \"transformers\",\n",
520 " \"CLIPImageProcessor\"\n",
521 " ],\n",
522 " \"image_encoder\": [\n",
523 " null,\n",
524 " null\n",
525 " ],\n",
526 " \"requires_safety_checker\": false,\n",
527 " \"safety_checker\": [\n",
528 " null,\n",
529 " null\n",
530 " ],\n",
531 " \"scheduler\": [\n",
532 " \"diffusers\",\n",
533 " \"DDIMScheduler\"\n",
534 " ],\n",
535 " \"text_encoder\": [\n",
536 " \"transformers\",\n",
537 " \"CLIPTextModel\"\n",
538 " ],\n",
539 " \"tokenizer\": [\n",
540 " \"transformers\",\n",
541 " \"CLIPTokenizer\"\n",
542 " ],\n",
543 " \"unet\": [\n",
544 " \"diffusers\",\n",
545 " \"UNet2DConditionModel\"\n",
546 " ],\n",
547 " \"vae\": [\n",
548 " \"diffusers\",\n",
549 " \"AutoencoderKL\"\n",
550 " ]\n",
551 "}"
552 ]
553 },
554 "execution_count": 2,
555 "metadata": {},
556 "output_type": "execute_result"
557 }
558 ],
559 "source": [
560 "from diffusers import StableDiffusionPipeline\n",
561 "import torch\n",
562 "\n",
563 "# Use a valid model name from Hugging Face\n",
564 "pipe = StableDiffusionPipeline.from_pretrained(\"stabilityai/stable-diffusion-2\", torch_dtype=torch.float16)\n",
565 "pipe.to(\"cuda\") # Ensure you're using a GPU for faster inferencec"
566 ]
567 },
568 {
569 "cell_type": "code",
570 "execution_count": 1,
571 "metadata": {
572 "colab": {
573 "base_uri": "https://localhost:8080/"
574 },
575 "executionInfo": {
576 "elapsed": 3515,
577 "status": "ok",
578 "timestamp": 1736782732269,
579 "user": {
580 "displayName": "Maham Ahmad",
581 "userId": "04446938859370329711"
582 },
583 "user_tz": -300
584 },
585 "id": "n6DMKbYWTGbd",
586 "outputId": "2487d668-2b4e-442c-c6d0-5b5a5c2155f4"
587 },
588 "outputs": [
589 {
590 "name": "stdout",
591 "output_type": "stream",
592 "text": [
593 "True\n",
594 "Tesla T4\n"
595 ]
596 }
597 ],
598 "source": [
599 "import torch\n",
600 "print(torch.cuda.is_available()) # Should print True if GPU is available\n",
601 "print(torch.cuda.get_device_name(0)) # Should print the GPU name, e.g., \"Tesla T4\""
602 ]
603 },
604 {
605 "cell_type": "code",
606 "execution_count": 3,
607 "metadata": {
608 "colab": {
609 "base_uri": "https://localhost:8080/",
610 "height": 1000,
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