Added json

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+env/
+venv/
+ENV/
+.venv
+
+# Model checkpoints
+*.pt
+*.pth
+*.ckpt
+best_model.pt
+
+# ImageNet classes (downloaded automatically)
+# imagenet_classes.json
+
+# Gradio cache
+.gradio/
+flagged/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Logs
+*.log
+

QUICKSTART.md

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+# Quick Start Guide - ResNet-50 ImageNet-1k Classifier
+
+## 🚀 Getting Started
+
+### Option 1: Test Locally (Without Training)
+
+```bash
+# 1. Install dependencies
+pip install -r requirements.txt
+
+# 2. Test the model architecture
+python test_model.py
+
+# 3. Run the Gradio app (with random weights for demo)
+python app.py
+```
+
+The app will automatically download ImageNet class labels from HuggingFace on first run.
+
+### Option 2: With Trained Model
+
+```bash
+# 1. Clone and set up training repository
+git clone https://github.com/arghyaiitb/assignment_9
+cd assignment_9
+
+# 2. Train the model (quick test with partial dataset)
+python main.py train --partial-dataset --partial-size 5000 --use-ffcv --epochs 5
+
+# OR train for full accuracy (requires GPUs)
+python main.py distributed --use-ffcv --batch-size 2048 --epochs 100 --progressive-resize --use-ema --compile
+
+# 3. Copy the trained checkpoint
+cp best_model.pt ../resnet50-imagenet-1k/
+
+# 4. Run the app with trained weights
+cd ../resnet50-imagenet-1k
+python app.py
+```
+
+## 📤 Deploy to HuggingFace Spaces
+
+### Method 1: Using Git
+
+```bash
+# 1. Create a new Space on HuggingFace (https://huggingface.co/new-space)
+#    Choose: Gradio SDK, Python 3.10+
+
+# 2. Clone your space
+git clone https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
+cd YOUR_SPACE_NAME
+
+# 3. Copy all files
+cp ../resnet50-imagenet-1k/* .
+
+# 4. Add your trained model (optional, but recommended)
+cp ../path/to/best_model.pt .
+
+# 5. Push to HuggingFace
+git add .
+git commit -m "Initial commit: ResNet-50 ImageNet classifier"
+git push
+```
+
+### Method 2: Using HuggingFace Hub
+
+```bash
+# 1. Install huggingface_hub
+pip install huggingface_hub
+
+# 2. Login
+huggingface-cli login
+
+# 3. Upload files
+python -c "
+from huggingface_hub import HfApi
+api = HfApi()
+api.upload_folder(
+    folder_path='.',
+    repo_id='YOUR_USERNAME/resnet50-imagenet-1k',
+    repo_type='space'
+)
+"
+```
+
+## 🔧 Troubleshooting
+
+### "Module not found" errors
+```bash
+pip install -r requirements.txt
+```
+
+### "Model checkpoint not found" warning
+This is normal if you haven't trained the model yet. The app will work with random weights for demonstration purposes.
+
+### Out of memory during training
+Reduce batch size:
+```bash
+python main.py train --batch-size 512 --epochs 100
+```
+
+### ImageNet classes not loading
+The app will automatically download them from HuggingFace. Ensure you have internet connection on first run.
+
+## 📊 Expected Performance
+
+| Configuration | Top-1 Acc | Top-5 Acc | Training Time |
+|--------------|-----------|-----------|---------------|
+| Random Init  | ~0.1%     | ~0.5%     | N/A           |
+| Partial (5k) | ~5-10%    | ~20-30%   | ~5 min        |
+| Full Training| 78%+      | 94%+      | ~90 min (8xA100) |
+
+## 📚 Additional Resources
+
+- **Training Code**: https://github.com/arghyaiitb/assignment_9
+- **HuggingFace Labels**: https://huggingface.co/datasets/huggingface/label-files
+- **Original Paper**: [Deep Residual Learning for Image Recognition (He et al., 2016)](https://arxiv.org/abs/1512.03385)
+
+## 🆘 Need Help?
+
+- Check the [training repository](https://github.com/arghyaiitb/assignment_9) for detailed training instructions
+- Verify your Python version: `python --version` (requires 3.8+)
+- Check installed packages: `pip list | grep -E "(torch|gradio)"`
+

imagenet_classes.json

@@ -0,0 +1,1002 @@
+{
+  "0": "tench, Tinca tinca",
+  "1": "goldfish, Carassius auratus",
+  "2": "great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias",
+  "3": "tiger shark, Galeocerdo cuvieri",
+  "4": "hammerhead, hammerhead shark",
+  "5": "electric ray, crampfish, numbfish, torpedo",
+  "6": "stingray",
+  "7": "cock",
+  "8": "hen",
+  "9": "ostrich, Struthio camelus",
+  "10": "brambling, Fringilla montifringilla",
+  "11": "goldfinch, Carduelis carduelis",
+  "12": "house finch, linnet, Carpodacus mexicanus",
+  "13": "junco, snowbird",
+  "14": "indigo bunting, indigo finch, indigo bird, Passerina cyanea",
+  "15": "robin, American robin, Turdus migratorius",
+  "16": "bulbul",
+  "17": "jay",
+  "18": "magpie",
+  "19": "chickadee",
+  "20": "water ouzel, dipper",
+  "21": "kite",
+  "22": "bald eagle, American eagle, Haliaeetus leucocephalus",
+  "23": "vulture",
+  "24": "great grey owl, great gray owl, Strix nebulosa",
+  "25": "European fire salamander, Salamandra salamandra",
+  "26": "common newt, Triturus vulgaris",
+  "27": "eft",
+  "28": "spotted salamander, Ambystoma maculatum",
+  "29": "axolotl, mud puppy, Ambystoma mexicanum",
+  "30": "bullfrog, Rana catesbeiana",
+  "31": "tree frog, tree-frog",
+  "32": "tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui",
+  "33": "loggerhead, loggerhead turtle, Caretta caretta",
+  "34": "leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea",
+  "35": "mud turtle",
+  "36": "terrapin",
+  "37": "box turtle, box tortoise",
+  "38": "banded gecko",
+  "39": "common iguana, iguana, Iguana iguana",
+  "40": "American chameleon, anole, Anolis carolinensis",
+  "41": "whiptail, whiptail lizard",
+  "42": "agama",
+  "43": "frilled lizard, Chlamydosaurus kingi",
+  "44": "alligator lizard",
+  "45": "Gila monster, Heloderma suspectum",
+  "46": "green lizard, Lacerta viridis",
+  "47": "African chameleon, Chamaeleo chamaeleon",
+  "48": "Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis",
+  "49": "African crocodile, Nile crocodile, Crocodylus niloticus",
+  "50": "American alligator, Alligator mississipiensis",
+  "51": "triceratops",
+  "52": "thunder snake, worm snake, Carphophis amoenus",
+  "53": "ringneck snake, ring-necked snake, ring snake",
+  "54": "hognose snake, puff adder, sand viper",
+  "55": "green snake, grass snake",
+  "56": "king snake, kingsnake",
+  "57": "garter snake, grass snake",
+  "58": "water snake",
+  "59": "vine snake",
+  "60": "night snake, Hypsiglena torquata",
+  "61": "boa constrictor, Constrictor constrictor",
+  "62": "rock python, rock snake, Python sebae",
+  "63": "Indian cobra, Naja naja",
+  "64": "green mamba",
+  "65": "sea snake",
+  "66": "horned viper, cerastes, sand viper, horned asp, Cerastes cornutus",
+  "67": "diamondback, diamondback rattlesnake, Crotalus adamanteus",
+  "68": "sidewinder, horned rattlesnake, Crotalus cerastes",
+  "69": "trilobite",
+  "70": "harvestman, daddy longlegs, Phalangium opilio",
+  "71": "scorpion",
+  "72": "black and gold garden spider, Argiope aurantia",
+  "73": "barn spider, Araneus cavaticus",
+  "74": "garden spider, Aranea diademata",
+  "75": "black widow, Latrodectus mactans",
+  "76": "tarantula",
+  "77": "wolf spider, hunting spider",
+  "78": "tick",
+  "79": "centipede",
+  "80": "black grouse",
+  "81": "ptarmigan",
+  "82": "ruffed grouse, partridge, Bonasa umbellus",
+  "83": "prairie chicken, prairie grouse, prairie fowl",
+  "84": "peacock",
+  "85": "quail",
+  "86": "partridge",
+  "87": "African grey, African gray, Psittacus erithacus",
+  "88": "macaw",
+  "89": "sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita",
+  "90": "lorikeet",
+  "91": "coucal",
+  "92": "bee eater",
+  "93": "hornbill",
+  "94": "hummingbird",
+  "95": "jacamar",
+  "96": "toucan",
+  "97": "drake",
+  "98": "red-breasted merganser, Mergus serrator",
+  "99": "goose",
+  "100": "black swan, Cygnus atratus",
+  "101": "tusker",
+  "102": "echidna, spiny anteater, anteater",
+  "103": "platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus",
+  "104": "wallaby, brush kangaroo",
+  "105": "koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus",
+  "106": "wombat",
+  "107": "jellyfish",
+  "108": "sea anemone, anemone",
+  "109": "brain coral",
+  "110": "flatworm, platyhelminth",
+  "111": "nematode, nematode worm, roundworm",
+  "112": "conch",
+  "113": "snail",
+  "114": "slug",
+  "115": "sea slug, nudibranch",
+  "116": "chiton, coat-of-mail shell, sea cradle, polyplacophore",
+  "117": "chambered nautilus, pearly nautilus, nautilus",
+  "118": "Dungeness crab, Cancer magister",
+  "119": "rock crab, Cancer irroratus",
+  "120": "fiddler crab",
+  "121": "king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica",
+  "122": "American lobster, Northern lobster, Maine lobster, Homarus americanus",
+  "123": "spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish",
+  "124": "crayfish, crawfish, crawdad, crawdaddy",
+  "125": "hermit crab",
+  "126": "isopod",
+  "127": "white stork, Ciconia ciconia",
+  "128": "black stork, Ciconia nigra",
+  "129": "spoonbill",
+  "130": "flamingo",
+  "131": "little blue heron, Egretta caerulea",
+  "132": "American egret, great white heron, Egretta albus",
+  "133": "bittern",
+  "134": "crane",
+  "135": "limpkin, Aramus pictus",
+  "136": "European gallinule, Porphyrio porphyrio",
+  "137": "American coot, marsh hen, mud hen, water hen, Fulica americana",
+  "138": "bustard",
+  "139": "ruddy turnstone, Arenaria interpres",
+  "140": "red-backed sandpiper, dunlin, Erolia alpina",
+  "141": "redshank, Tringa totanus",
+  "142": "dowitcher",
+  "143": "oystercatcher, oyster catcher",
+  "144": "pelican",
+  "145": "king penguin, Aptenodytes patagonica",
+  "146": "albatross, mollymawk",
+  "147": "grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus",
+  "148": "killer whale, killer, orca, grampus, sea wolf, Orcinus orca",
+  "149": "dugong, Dugong dugon",
+  "150": "sea lion",
+  "151": "Chihuahua",
+  "152": "Japanese spaniel",
+  "153": "Maltese dog, Maltese terrier, Maltese",
+  "154": "Pekinese, Pekingese, Peke",
+  "155": "Shih-Tzu",
+  "156": "Blenheim spaniel",
+  "157": "papillon",
+  "158": "toy terrier",
+  "159": "Rhodesian ridgeback",
+  "160": "Afghan hound, Afghan",
+  "161": "basset, basset hound",
+  "162": "beagle",
+  "163": "bloodhound, sleuthhound",
+  "164": "bluetick",
+  "165": "black-and-tan coonhound",
+  "166": "Walker hound, Walker foxhound",
+  "167": "English foxhound",
+  "168": "redbone",
+  "169": "borzoi, Russian wolfhound",
+  "170": "Irish wolfhound",
+  "171": "Italian greyhound",
+  "172": "whippet",
+  "173": "Ibizan hound, Ibizan Podenco",
+  "174": "Norwegian elkhound, elkhound",
+  "175": "otterhound, otter hound",
+  "176": "Saluki, gazelle hound",
+  "177": "Scottish deerhound, deerhound",
+  "178": "Weimaraner",
+  "179": "Staffordshire bullterrier, Staffordshire bull terrier",
+  "180": "American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier",
+  "181": "Bedlington terrier",
+  "182": "Border terrier",
+  "183": "Kerry blue terrier",
+  "184": "Irish terrier",
+  "185": "Norfolk terrier",
+  "186": "Norwich terrier",
+  "187": "Yorkshire terrier",
+  "188": "wire-haired fox terrier",
+  "189": "Lakeland terrier",
+  "190": "Sealyham terrier, Sealyham",
+  "191": "Airedale, Airedale terrier",
+  "192": "cairn, cairn terrier",
+  "193": "Australian terrier",
+  "194": "Dandie Dinmont, Dandie Dinmont terrier",
+  "195": "Boston bull, Boston terrier",
+  "196": "miniature schnauzer",
+  "197": "giant schnauzer",
+  "198": "standard schnauzer",
+  "199": "Scotch terrier, Scottish terrier, Scottie",
+  "200": "Tibetan terrier, chrysanthemum dog",
+  "201": "silky terrier, Sydney silky",
+  "202": "soft-coated wheaten terrier",
+  "203": "West Highland white terrier",
+  "204": "Lhasa, Lhasa apso",
+  "205": "flat-coated retriever",
+  "206": "curly-coated retriever",
+  "207": "golden retriever",
+  "208": "Labrador retriever",
+  "209": "Chesapeake Bay retriever",
+  "210": "German short-haired pointer",
+  "211": "vizsla, Hungarian pointer",
+  "212": "English setter",
+  "213": "Irish setter, red setter",
+  "214": "Gordon setter",
+  "215": "Brittany spaniel",
+  "216": "clumber, clumber spaniel",
+  "217": "English springer, English springer spaniel",
+  "218": "Welsh springer spaniel",
+  "219": "cocker spaniel, English cocker spaniel, cocker",
+  "220": "Sussex spaniel",
+  "221": "Irish water spaniel",
+  "222": "kuvasz",
+  "223": "schipperke",
+  "224": "groenendael",
+  "225": "malinois",
+  "226": "briard",
+  "227": "kelpie",
+  "228": "komondor",
+  "229": "Old English sheepdog, bobtail",
+  "230": "Shetland sheepdog, Shetland sheep dog, Shetland",
+  "231": "collie",
+  "232": "Border collie",
+  "233": "Bouvier des Flandres, Bouviers des Flandres",
+  "234": "Rottweiler",
+  "235": "German shepherd, German shepherd dog, German police dog, alsatian",
+  "236": "Doberman, Doberman pinscher",
+  "237": "miniature pinscher",
+  "238": "Greater Swiss Mountain dog",
+  "239": "Bernese mountain dog",
+  "240": "Appenzeller",
+  "241": "EntleBucher",
+  "242": "boxer",
+  "243": "bull mastiff",
+  "244": "Tibetan mastiff",
+  "245": "French bulldog",
+  "246": "Great Dane",
+  "247": "Saint Bernard, St Bernard",
+  "248": "Eskimo dog, husky",
+  "249": "malamute, malemute, Alaskan malamute",
+  "250": "Siberian husky",
+  "251": "dalmatian, coach dog, carriage dog",
+  "252": "affenpinscher, monkey pinscher, monkey dog",
+  "253": "basenji",
+  "254": "pug, pug-dog",
+  "255": "Leonberg",
+  "256": "Newfoundland, Newfoundland dog",
+  "257": "Great Pyrenees",
+  "258": "Samoyed, Samoyede",
+  "259": "Pomeranian",
+  "260": "chow, chow chow",
+  "261": "keeshond",
+  "262": "Brabancon griffon",
+  "263": "Pembroke, Pembroke Welsh corgi",
+  "264": "Cardigan, Cardigan Welsh corgi",
+  "265": "toy poodle",
+  "266": "miniature poodle",
+  "267": "standard poodle",
+  "268": "Mexican hairless",
+  "269": "timber wolf, grey wolf, gray wolf, Canis lupus",
+  "270": "white wolf, Arctic wolf, Canis lupus tundrarum",
+  "271": "red wolf, maned wolf, Canis rufus, Canis niger",
+  "272": "coyote, prairie wolf, brush wolf, Canis latrans",
+  "273": "dingo, warrigal, warragal, Canis dingo",
+  "274": "dhole, Cuon alpinus",
+  "275": "African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus",
+  "276": "hyena, hyaena",
+  "277": "red fox, Vulpes vulpes",
+  "278": "kit fox, Vulpes macrotis",
+  "279": "Arctic fox, white fox, Alopex lagopus",
+  "280": "grey fox, gray fox, Urocyon cinereoargenteus",
+  "281": "tabby, tabby cat",
+  "282": "tiger cat",
+  "283": "Persian cat",
+  "284": "Siamese cat, Siamese",
+  "285": "Egyptian cat",
+  "286": "cougar, puma, catamount, mountain lion, painter, panther, Felis concolor",
+  "287": "lynx, catamount",
+  "288": "leopard, Panthera pardus",
+  "289": "snow leopard, ounce, Panthera uncia",
+  "290": "jaguar, panther, Panthera onca, Felis onca",
+  "291": "lion, king of beasts, Panthera leo",
+  "292": "tiger, Panthera tigris",
+  "293": "cheetah, chetah, Acinonyx jubatus",
+  "294": "brown bear, bruin, Ursus arctos",
+  "295": "American black bear, black bear, Ursus americanus, Euarctos americanus",
+  "296": "ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus",
+  "297": "sloth bear, Melursus ursinus, Ursus ursinus",
+  "298": "mongoose",
+  "299": "meerkat, mierkat",
+  "300": "tiger beetle",
+  "301": "ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle",
+  "302": "ground beetle, carabid beetle",
+  "303": "long-horned beetle, longicorn, longicorn beetle",
+  "304": "leaf beetle, chrysomelid",
+  "305": "dung beetle",
+  "306": "rhinoceros beetle",
+  "307": "weevil",
+  "308": "fly",
+  "309": "bee",
+  "310": "ant, emmet, pismire",
+  "311": "grasshopper, hopper",
+  "312": "cricket",
+  "313": "walking stick, walkingstick, stick insect",
+  "314": "cockroach, roach",
+  "315": "mantis, mantid",
+  "316": "cicada, cicala",
+  "317": "leafhopper",
+  "318": "lacewing, lacewing fly",
+  "319": "dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk",
+  "320": "damselfly",
+  "321": "admiral",
+  "322": "ringlet, ringlet butterfly",
+  "323": "monarch, monarch butterfly, milkweed butterfly, Danaus plexippus",
+  "324": "cabbage butterfly",
+  "325": "sulphur butterfly, sulfur butterfly",
+  "326": "lycaenid, lycaenid butterfly",
+  "327": "starfish, sea star",
+  "328": "sea urchin",
+  "329": "sea cucumber, holothurian",
+  "330": "wood rabbit, cottontail, cottontail rabbit",
+  "331": "hare",
+  "332": "Angora, Angora rabbit",
+  "333": "hamster",
+  "334": "porcupine, hedgehog",
+  "335": "fox squirrel, eastern fox squirrel, Sciurus niger",
+  "336": "marmot",
+  "337": "beaver",
+  "338": "guinea pig, Cavia cobaya",
+  "339": "sorrel",
+  "340": "zebra",
+  "341": "hog, pig, grunter, squealer, Sus scrofa",
+  "342": "wild boar, boar, Sus scrofa",
+  "343": "warthog",
+  "344": "hippopotamus, hippo, river horse, Hippopotamus amphibius",
+  "345": "ox",
+  "346": "water buffalo, water ox, Asiatic buffalo, Bubalus bubalis",
+  "347": "bison",
+  "348": "ram, tup",
+  "349": "bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis",
+  "350": "ibex, Capra ibex",
+  "351": "hartebeest",
+  "352": "impala, Aepyceros melampus",
+  "353": "gazelle",
+  "354": "Arabian camel, dromedary, Camelus dromedarius",
+  "355": "llama",
+  "356": "weasel",
+  "357": "mink",
+  "358": "polecat, fitch, foulmart, foumart, Mustela putorius",
+  "359": "black-footed ferret, ferret, Mustela nigripes",
+  "360": "otter",
+  "361": "skunk, polecat, wood pussy",
+  "362": "badger",
+  "363": "armadillo",
+  "364": "three-toed sloth, ai, Bradypus tridactylus",
+  "365": "orangutan, orang, orangutang, Pongo pygmaeus",
+  "366": "gorilla, Gorilla gorilla",
+  "367": "chimpanzee, chimp, Pan troglodytes",
+  "368": "gibbon, Hylobates lar",
+  "369": "siamang, Hylobates syndactylus, Symphalangus syndactylus",
+  "370": "guenon, guenon monkey",
+  "371": "patas, hussar monkey, Erythrocebus patas",
+  "372": "baboon",
+  "373": "macaque",
+  "374": "langur",
+  "375": "colobus, colobus monkey",
+  "376": "proboscis monkey, Nasalis larvatus",
+  "377": "marmoset",
+  "378": "capuchin, ringtail, Cebus capucinus",
+  "379": "howler monkey, howler",
+  "380": "titi, titi monkey",
+  "381": "spider monkey, Ateles geoffroyi",
+  "382": "squirrel monkey, Saimiri sciureus",
+  "383": "Madagascar cat, ring-tailed lemur, Lemur catta",
+  "384": "indri, indris, Indri indri, Indri brevicaudatus",
+  "385": "Indian elephant, Elephas maximus",
+  "386": "African elephant, Loxodonta africana",
+  "387": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens",
+  "388": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
+  "389": "barracouta, snoek",
+  "390": "eel",
+  "391": "coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch",
+  "392": "rock beauty, Holocanthus tricolor",
+  "393": "anemone fish",
+  "394": "sturgeon",
+  "395": "gar, garfish, garpike, billfish, Lepisosteus osseus",
+  "396": "lionfish",
+  "397": "puffer, pufferfish, blowfish, globefish",
+  "398": "abacus",
+  "399": "abaya",
+  "400": "academic gown, academic robe, judge's robe",
+  "401": "accordion, piano accordion, squeeze box",
+  "402": "acoustic guitar",
+  "403": "aircraft carrier, carrier, flattop, attack aircraft carrier",
+  "404": "airliner",
+  "405": "airship, dirigible",
+  "406": "altar",
+  "407": "ambulance",
+  "408": "amphibian, amphibious vehicle",
+  "409": "analog clock",
+  "410": "apiary, bee house",
+  "411": "apron",
+  "412": "ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin",
+  "413": "assault rifle, assault gun",
+  "414": "backpack, back pack, knapsack, packsack, rucksack, haversack",
+  "415": "bakery, bakeshop, bakehouse",
+  "416": "balance beam, beam",
+  "417": "balloon",
+  "418": "ballpoint, ballpoint pen, ballpen, Biro",
+  "419": "Band Aid",
+  "420": "banjo",
+  "421": "bannister, banister, balustrade, balusters, handrail",
+  "422": "barbell",
+  "423": "barber chair",
+  "424": "barbershop",
+  "425": "barn",
+  "426": "barometer",
+  "427": "barrel, cask",
+  "428": "barrow, garden cart, lawn cart, wheelbarrow",
+  "429": "baseball",
+  "430": "basketball",
+  "431": "bassinet",
+  "432": "bassoon",
+  "433": "bathing cap, swimming cap",
+  "434": "bath towel",
+  "435": "bathtub, bathing tub, bath, tub",
+  "436": "beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon",
+  "437": "beacon, lighthouse, beacon light, pharos",
+  "438": "beaker",
+  "439": "bearskin, busby, shako",
+  "440": "beer bottle",
+  "441": "beer glass",
+  "442": "bell cote, bell cot",
+  "443": "bib",
+  "444": "bicycle-built-for-two, tandem bicycle, tandem",
+  "445": "bikini, two-piece",
+  "446": "binder, ring-binder",
+  "447": "binoculars, field glasses, opera glasses",
+  "448": "birdhouse",
+  "449": "boathouse",
+  "450": "bobsled, bobsleigh, bob",
+  "451": "bolo tie, bolo, bola tie, bola",
+  "452": "bonnet, poke bonnet",
+  "453": "bookcase",
+  "454": "bookshop, bookstore, bookstall",
+  "455": "bottlecap",
+  "456": "bow",
+  "457": "bow tie, bow-tie, bowtie",
+  "458": "brass, memorial tablet, plaque",
+  "459": "brassiere, bra, bandeau",
+  "460": "breakwater, groin, groyne, mole, bulwark, seawall, jetty",
+  "461": "breastplate, aegis, egis",
+  "462": "broom",
+  "463": "bucket, pail",
+  "464": "buckle",
+  "465": "bulletproof vest",
+  "466": "bullet train, bullet",
+  "467": "butcher shop, meat market",
+  "468": "cab, hack, taxi, taxicab",
+  "469": "caldron, cauldron",
+  "470": "candle, taper, wax light",
+  "471": "cannon",
+  "472": "canoe",
+  "473": "can opener, tin opener",
+  "474": "cardigan",
+  "475": "car mirror",
+  "476": "carousel, carrousel, merry-go-round, roundabout, whirligig",
+  "477": "carpenter's kit, tool kit",
+  "478": "carton",
+  "479": "car wheel",
+  "480": "cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM",
+  "481": "cassette",
+  "482": "cassette player",
+  "483": "castle",
+  "484": "catamaran",
+  "485": "CD player",
+  "486": "cello, violoncello",
+  "487": "cellular telephone, cellular phone, cellphone, cell, mobile phone",
+  "488": "chain",
+  "489": "chainlink fence",
+  "490": "chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour",
+  "491": "chain saw, chainsaw",
+  "492": "chest",
+  "493": "chiffonier, commode",
+  "494": "chime, bell, gong",
+  "495": "china cabinet, china closet",
+  "496": "Christmas stocking",
+  "497": "church, church building",
+  "498": "cinema, movie theater, movie theatre, movie house, picture palace",
+  "499": "cleaver, meat cleaver, chopper",
+  "500": "cliff dwelling",
+  "501": "cloak",
+  "502": "clog, geta, patten, sabot",
+  "503": "cocktail shaker",
+  "504": "coffee mug",
+  "505": "coffeepot",
+  "506": "coil, spiral, volute, whorl, helix",
+  "507": "combination lock",
+  "508": "computer keyboard, keypad",
+  "509": "confectionery, confectionary, candy store",
+  "510": "container ship, containership, container vessel",
+  "511": "convertible",
+  "512": "corkscrew, bottle screw",
+  "513": "cornet, horn, trumpet, trump",
+  "514": "cowboy boot",
+  "515": "cowboy hat, ten-gallon hat",
+  "516": "cradle",
+  "517": "crane",
+  "518": "crash helmet",
+  "519": "crate",
+  "520": "crib, cot",
+  "521": "Crock Pot",
+  "522": "croquet ball",
+  "523": "crutch",
+  "524": "cuirass",
+  "525": "dam, dike, dyke",
+  "526": "desk",
+  "527": "desktop computer",
+  "528": "dial telephone, dial phone",
+  "529": "diaper, nappy, napkin",
+  "530": "digital clock",
+  "531": "digital watch",
+  "532": "dining table, board",
+  "533": "dishrag, dishcloth",
+  "534": "dishwasher, dish washer, dishwashing machine",
+  "535": "disk brake, disc brake",
+  "536": "dock, dockage, docking facility",
+  "537": "dogsled, dog sled, dog sleigh",
+  "538": "dome",
+  "539": "doormat, welcome mat",
+  "540": "drilling platform, offshore rig",
+  "541": "drum, membranophone, tympan",
+  "542": "drumstick",
+  "543": "dumbbell",
+  "544": "Dutch oven",
+  "545": "electric fan, blower",
+  "546": "electric guitar",
+  "547": "electric locomotive",
+  "548": "entertainment center",
+  "549": "envelope",
+  "550": "espresso maker",
+  "551": "face powder",
+  "552": "feather boa, boa",
+  "553": "file, file cabinet, filing cabinet",
+  "554": "fireboat",
+  "555": "fire engine, fire truck",
+  "556": "fire screen, fireguard",
+  "557": "flagpole, flagstaff",
+  "558": "flute, transverse flute",
+  "559": "folding chair",
+  "560": "football helmet",
+  "561": "forklift",
+  "562": "fountain",
+  "563": "fountain pen",
+  "564": "four-poster",
+  "565": "freight car",
+  "566": "French horn, horn",
+  "567": "frying pan, frypan, skillet",
+  "568": "fur coat",
+  "569": "garbage truck, dustcart",
+  "570": "gasmask, respirator, gas helmet",
+  "571": "gas pump, gasoline pump, petrol pump, island dispenser",
+  "572": "goblet",
+  "573": "go-kart",
+  "574": "golf ball",
+  "575": "golfcart, golf cart",
+  "576": "gondola",
+  "577": "gong, tam-tam",
+  "578": "gown",
+  "579": "grand piano, grand",
+  "580": "greenhouse, nursery, glasshouse",
+  "581": "grille, radiator grille",
+  "582": "grocery store, grocery, food market, market",
+  "583": "guillotine",
+  "584": "hair slide",
+  "585": "hair spray",
+  "586": "half track",
+  "587": "hammer",
+  "588": "hamper",
+  "589": "hand blower, blow dryer, blow drier, hair dryer, hair drier",
+  "590": "hand-held computer, hand-held microcomputer",
+  "591": "handkerchief, hankie, hanky, hankey",
+  "592": "hard disc, hard disk, fixed disk",
+  "593": "harmonica, mouth organ, harp, mouth harp",
+  "594": "harp",
+  "595": "harvester, reaper",
+  "596": "hatchet",
+  "597": "holster",
+  "598": "home theater, home theatre",
+  "599": "honeycomb",
+  "600": "hook, claw",
+  "601": "hoopskirt, crinoline",
+  "602": "horizontal bar, high bar",
+  "603": "horse cart, horse-cart",
+  "604": "hourglass",
+  "605": "iPod",
+  "606": "iron, smoothing iron",
+  "607": "jack-o'-lantern",
+  "608": "jean, blue jean, denim",
+  "609": "jeep, landrover",
+  "610": "jersey, T-shirt, tee shirt",
+  "611": "jigsaw puzzle",
+  "612": "jinrikisha, ricksha, rickshaw",
+  "613": "joystick",
+  "614": "kimono",
+  "615": "knee pad",
+  "616": "knot",
+  "617": "lab coat, laboratory coat",
+  "618": "ladle",
+  "619": "lampshade, lamp shade",
+  "620": "laptop, laptop computer",
+  "621": "lawn mower, mower",
+  "622": "lens cap, lens cover",
+  "623": "letter opener, paper knife, paperknife",
+  "624": "library",
+  "625": "lifeboat",
+  "626": "lighter, light, igniter, ignitor",
+  "627": "limousine, limo",
+  "628": "liner, ocean liner",
+  "629": "lipstick, lip rouge",
+  "630": "Loafer",
+  "631": "lotion",
+  "632": "loudspeaker, speaker, speaker unit, loudspeaker system, speaker system",
+  "633": "loupe, jeweler's loupe",
+  "634": "lumbermill, sawmill",
+  "635": "magnetic compass",
+  "636": "mailbag, postbag",
+  "637": "mailbox, letter box",
+  "638": "maillot",
+  "639": "maillot, tank suit",
+  "640": "manhole cover",
+  "641": "maraca",
+  "642": "marimba, xylophone",
+  "643": "mask",
+  "644": "matchstick",
+  "645": "maypole",
+  "646": "maze, labyrinth",
+  "647": "measuring cup",
+  "648": "medicine chest, medicine cabinet",
+  "649": "megalith, megalithic structure",
+  "650": "microphone, mike",
+  "651": "microwave, microwave oven",
+  "652": "military uniform",
+  "653": "milk can",
+  "654": "minibus",
+  "655": "miniskirt, mini",
+  "656": "minivan",
+  "657": "missile",
+  "658": "mitten",
+  "659": "mixing bowl",
+  "660": "mobile home, manufactured home",
+  "661": "Model T",
+  "662": "modem",
+  "663": "monastery",
+  "664": "monitor",
+  "665": "moped",
+  "666": "mortar",
+  "667": "mortarboard",
+  "668": "mosque",
+  "669": "mosquito net",
+  "670": "motor scooter, scooter",
+  "671": "mountain bike, all-terrain bike, off-roader",
+  "672": "mountain tent",
+  "673": "mouse, computer mouse",
+  "674": "mousetrap",
+  "675": "moving van",
+  "676": "muzzle",
+  "677": "nail",
+  "678": "neck brace",
+  "679": "necklace",
+  "680": "nipple",
+  "681": "notebook, notebook computer",
+  "682": "obelisk",
+  "683": "oboe, hautboy, hautbois",
+  "684": "ocarina, sweet potato",
+  "685": "odometer, hodometer, mileometer, milometer",
+  "686": "oil filter",
+  "687": "organ, pipe organ",
+  "688": "oscilloscope, scope, cathode-ray oscilloscope, CRO",
+  "689": "overskirt",
+  "690": "oxcart",
+  "691": "oxygen mask",
+  "692": "packet",
+  "693": "paddle, boat paddle",
+  "694": "paddlewheel, paddle wheel",
+  "695": "padlock",
+  "696": "paintbrush",
+  "697": "pajama, pyjama, pj's, jammies",
+  "698": "palace",
+  "699": "panpipe, pandean pipe, syrinx",
+  "700": "paper towel",
+  "701": "parachute, chute",
+  "702": "parallel bars, bars",
+  "703": "park bench",
+  "704": "parking meter",
+  "705": "passenger car, coach, carriage",
+  "706": "patio, terrace",
+  "707": "pay-phone, pay-station",
+  "708": "pedestal, plinth, footstall",
+  "709": "pencil box, pencil case",
+  "710": "pencil sharpener",
+  "711": "perfume, essence",
+  "712": "Petri dish",
+  "713": "photocopier",
+  "714": "pick, plectrum, plectron",
+  "715": "pickelhaube",
+  "716": "picket fence, paling",
+  "717": "pickup, pickup truck",
+  "718": "pier",
+  "719": "piggy bank, penny bank",
+  "720": "pill bottle",
+  "721": "pillow",
+  "722": "ping-pong ball",
+  "723": "pinwheel",
+  "724": "pirate, pirate ship",
+  "725": "pitcher, ewer",
+  "726": "plane, carpenter's plane, woodworking plane",
+  "727": "planetarium",
+  "728": "plastic bag",
+  "729": "plate rack",
+  "730": "plow, plough",
+  "731": "plunger, plumber's helper",
+  "732": "Polaroid camera, Polaroid Land camera",
+  "733": "pole",
+  "734": "police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria",
+  "735": "poncho",
+  "736": "pool table, billiard table, snooker table",
+  "737": "pop bottle, soda bottle",
+  "738": "pot, flowerpot",
+  "739": "potter's wheel",
+  "740": "power drill",
+  "741": "prayer rug, prayer mat",
+  "742": "printer",
+  "743": "prison, prison house",
+  "744": "projectile, missile",
+  "745": "projector",
+  "746": "puck, hockey puck",
+  "747": "punching bag, punch bag, punching ball, punchball",
+  "748": "purse",
+  "749": "quill, quill pen",
+  "750": "quilt, comforter, comfort, puff",
+  "751": "racer, race car, racing car",
+  "752": "racket, racquet",
+  "753": "radiator",
+  "754": "radio, wireless",
+  "755": "radio telescope, radio reflector",
+  "756": "rain barrel",
+  "757": "recreational vehicle, RV, R.V.",
+  "758": "reel",
+  "759": "reflex camera",
+  "760": "refrigerator, icebox",
+  "761": "remote control, remote",
+  "762": "restaurant, eating house, eating place, eatery",
+  "763": "revolver, six-gun, six-shooter",
+  "764": "rifle",
+  "765": "rocking chair, rocker",
+  "766": "rotisserie",
+  "767": "rubber eraser, rubber, pencil eraser",
+  "768": "rugby ball",
+  "769": "rule, ruler",
+  "770": "running shoe",
+  "771": "safe",
+  "772": "safety pin",
+  "773": "saltshaker, salt shaker",
+  "774": "sandal",
+  "775": "sarong",
+  "776": "sax, saxophone",
+  "777": "scabbard",
+  "778": "scale, weighing machine",
+  "779": "school bus",
+  "780": "schooner",
+  "781": "scoreboard",
+  "782": "screen, CRT screen",
+  "783": "screw",
+  "784": "screwdriver",
+  "785": "seat belt, seatbelt",
+  "786": "sewing machine",
+  "787": "shield, buckler",
+  "788": "shoe shop, shoe-shop, shoe store",
+  "789": "shoji",
+  "790": "shopping basket",
+  "791": "shopping cart",
+  "792": "shovel",
+  "793": "shower cap",
+  "794": "shower curtain",
+  "795": "ski",
+  "796": "ski mask",
+  "797": "sleeping bag",
+  "798": "slide rule, slipstick",
+  "799": "sliding door",
+  "800": "slot, one-armed bandit",
+  "801": "snorkel",
+  "802": "snowmobile",
+  "803": "snowplow, snowplough",
+  "804": "soap dispenser",
+  "805": "soccer ball",
+  "806": "sock",
+  "807": "solar dish, solar collector, solar furnace",
+  "808": "sombrero",
+  "809": "soup bowl",
+  "810": "space bar",
+  "811": "space heater",
+  "812": "space shuttle",
+  "813": "spatula",
+  "814": "speedboat",
+  "815": "spider web, spider's web",
+  "816": "spindle",
+  "817": "sports car, sport car",
+  "818": "spotlight, spot",
+  "819": "stage",
+  "820": "steam locomotive",
+  "821": "steel arch bridge",
+  "822": "steel drum",
+  "823": "stethoscope",
+  "824": "stole",
+  "825": "stone wall",
+  "826": "stopwatch, stop watch",
+  "827": "stove",
+  "828": "strainer",
+  "829": "streetcar, tram, tramcar, trolley, trolley car",
+  "830": "stretcher",
+  "831": "studio couch, day bed",
+  "832": "stupa, tope",
+  "833": "submarine, pigboat, sub, U-boat",
+  "834": "suit, suit of clothes",
+  "835": "sundial",
+  "836": "sunglass",
+  "837": "sunglasses, dark glasses, shades",
+  "838": "sunscreen, sunblock, sun blocker",
+  "839": "suspension bridge",
+  "840": "swab, swob, mop",
+  "841": "sweatshirt",
+  "842": "swimming trunks, bathing trunks",
+  "843": "swing",
+  "844": "switch, electric switch, electrical switch",
+  "845": "syringe",
+  "846": "table lamp",
+  "847": "tank, army tank, armored combat vehicle, armoured combat vehicle",
+  "848": "tape player",
+  "849": "teapot",
+  "850": "teddy, teddy bear",
+  "851": "television, television system",
+  "852": "tennis ball",
+  "853": "thatch, thatched roof",
+  "854": "theater curtain, theatre curtain",
+  "855": "thimble",
+  "856": "thresher, thrasher, threshing machine",
+  "857": "throne",
+  "858": "tile roof",
+  "859": "toaster",
+  "860": "tobacco shop, tobacconist shop, tobacconist",
+  "861": "toilet seat",
+  "862": "torch",
+  "863": "totem pole",
+  "864": "tow truck, tow car, wrecker",
+  "865": "toyshop",
+  "866": "tractor",
+  "867": "trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi",
+  "868": "tray",
+  "869": "trench coat",
+  "870": "tricycle, trike, velocipede",
+  "871": "trimaran",
+  "872": "tripod",
+  "873": "triumphal arch",
+  "874": "trolleybus, trolley coach, trackless trolley",
+  "875": "trombone",
+  "876": "tub, vat",
+  "877": "turnstile",
+  "878": "typewriter keyboard",
+  "879": "umbrella",
+  "880": "unicycle, monocycle",
+  "881": "upright, upright piano",
+  "882": "vacuum, vacuum cleaner",
+  "883": "vase",
+  "884": "vault",
+  "885": "velvet",
+  "886": "vending machine",
+  "887": "vestment",
+  "888": "viaduct",
+  "889": "violin, fiddle",
+  "890": "volleyball",
+  "891": "waffle iron",
+  "892": "wall clock",
+  "893": "wallet, billfold, notecase, pocketbook",
+  "894": "wardrobe, closet, press",
+  "895": "warplane, military plane",
+  "896": "washbasin, handbasin, washbowl, lavabo, wash-hand basin",
+  "897": "washer, automatic washer, washing machine",
+  "898": "water bottle",
+  "899": "water jug",
+  "900": "water tower",
+  "901": "whiskey jug",
+  "902": "whistle",
+  "903": "wig",
+  "904": "window screen",
+  "905": "window shade",
+  "906": "Windsor tie",
+  "907": "wine bottle",
+  "908": "wing",
+  "909": "wok",
+  "910": "wooden spoon",
+  "911": "wool, woolen, woollen",
+  "912": "worm fence, snake fence, snake-rail fence, Virginia fence",
+  "913": "wreck",
+  "914": "yawl",
+  "915": "yurt",
+  "916": "web site, website, internet site, site",
+  "917": "comic book",
+  "918": "crossword puzzle, crossword",
+  "919": "street sign",
+  "920": "traffic light, traffic signal, stoplight",
+  "921": "book jacket, dust cover, dust jacket, dust wrapper",
+  "922": "menu",
+  "923": "plate",
+  "924": "guacamole",
+  "925": "consomme",
+  "926": "hot pot, hotpot",
+  "927": "trifle",
+  "928": "ice cream, icecream",
+  "929": "ice lolly, lolly, lollipop, popsicle",
+  "930": "French loaf",
+  "931": "bagel, beigel",
+  "932": "pretzel",
+  "933": "cheeseburger",
+  "934": "hotdog, hot dog, red hot",
+  "935": "mashed potato",
+  "936": "head cabbage",
+  "937": "broccoli",
+  "938": "cauliflower",
+  "939": "zucchini, courgette",
+  "940": "spaghetti squash",
+  "941": "acorn squash",
+  "942": "butternut squash",
+  "943": "cucumber, cuke",
+  "944": "artichoke, globe artichoke",
+  "945": "bell pepper",
+  "946": "cardoon",
+  "947": "mushroom",
+  "948": "Granny Smith",
+  "949": "strawberry",
+  "950": "orange",
+  "951": "lemon",
+  "952": "fig",
+  "953": "pineapple, ananas",
+  "954": "banana",
+  "955": "jackfruit, jak, jack",
+  "956": "custard apple",
+  "957": "pomegranate",
+  "958": "hay",
+  "959": "carbonara",
+  "960": "chocolate sauce, chocolate syrup",
+  "961": "dough",
+  "962": "meat loaf, meatloaf",
+  "963": "pizza, pizza pie",
+  "964": "potpie",
+  "965": "burrito",
+  "966": "red wine",
+  "967": "espresso",
+  "968": "cup",
+  "969": "eggnog",
+  "970": "alp",
+  "971": "bubble",
+  "972": "cliff, drop, drop-off",
+  "973": "coral reef",
+  "974": "geyser",
+  "975": "lakeside, lakeshore",
+  "976": "promontory, headland, head, foreland",
+  "977": "sandbar, sand bar",
+  "978": "seashore, coast, seacoast, sea-coast",
+  "979": "valley, vale",
+  "980": "volcano",
+  "981": "ballplayer, baseball player",
+  "982": "groom, bridegroom",
+  "983": "scuba diver",
+  "984": "rapeseed",
+  "985": "daisy",
+  "986": "yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum",
+  "987": "corn",
+  "988": "acorn",
+  "989": "hip, rose hip, rosehip",
+  "990": "buckeye, horse chestnut, conker",
+  "991": "coral fungus",
+  "992": "agaric",
+  "993": "gyromitra",
+  "994": "stinkhorn, carrion fungus",
+  "995": "earthstar",
+  "996": "hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa",
+  "997": "bolete",
+  "998": "ear, spike, capitulum",
+  "999": "toilet tissue, toilet paper, bathroom tissue"
+}

test_model.py

@@ -0,0 +1,124 @@
+"""
+Test script to verify ResNet-50 model architecture and predictions
+"""
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from PIL import Image
+import requests
+from io import BytesIO
+import json
+
+# Import model from app.py
+import sys
+sys.path.append('.')
+
+print("=" * 60)
+print("ResNet-50 ImageNet Model Test")
+print("=" * 60)
+
+# Load model architecture from app.py
+from app import ResNet50, transform, IMAGENET_CLASSES
+
+# Create model
+model = ResNet50(num_classes=1000)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+model.eval()
+
+# Test 1: Model architecture
+print("\n✓ Test 1: Model Architecture")
+print(f"  - Total parameters: {sum(p.numel() for p in model.parameters()):,}")
+print(f"  - Trainable parameters: {sum(p.numel() for p in model.parameters() if p.requires_grad):,}")
+print(f"  - Device: {device}")
+
+# Expected parameters for ResNet-50: ~25.6M
+total_params = sum(p.numel() for p in model.parameters())
+expected_params = 25_557_032  # Standard ResNet-50
+if abs(total_params - expected_params) < 100000:  # Allow some variance
+    print(f"  ✓ Parameter count matches expected ResNet-50 (~25.6M)")
+else:
+    print(f"  ⚠ Parameter count differs from standard ResNet-50")
+    print(f"    Expected: ~{expected_params:,}, Got: {total_params:,}")
+
+# Test 2: Forward pass with dummy input
+print("\n✓ Test 2: Forward Pass")
+dummy_input = torch.randn(1, 3, 224, 224).to(device)
+with torch.no_grad():
+    output = model(dummy_input)
+print(f"  - Input shape: {dummy_input.shape}")
+print(f"  - Output shape: {output.shape}")
+print(f"  - Expected output shape: torch.Size([1, 1000])")
+assert output.shape == torch.Size([1, 1000]), "Output shape mismatch!"
+print(f"  ✓ Output shape is correct")
+
+# Test 3: Test with a sample image (if available online)
+print("\n✓ Test 3: Sample Prediction")
+try:
+    # Download a sample image (Golden Retriever)
+    url = "https://images.unsplash.com/photo-1633722715463-d30f4f325e24?w=400"
+    response = requests.get(url, timeout=10)
+    img = Image.open(BytesIO(response.content)).convert('RGB')
+    
+    # Preprocess
+    img_tensor = transform(img).unsqueeze(0).to(device)
+    
+    # Predict
+    with torch.no_grad():
+        outputs = model(img_tensor)
+        probabilities = F.softmax(outputs, dim=1)[0]
+    
+    # Get top 5
+    top5_prob, top5_idx = torch.topk(probabilities, 5)
+    
+    print(f"  - Image size: {img.size}")
+    print(f"  - Top 5 predictions:")
+    for i, (idx, prob) in enumerate(zip(top5_idx, top5_prob), 1):
+        class_name = IMAGENET_CLASSES.get(str(idx.item()), f"Class {idx.item()}")
+        print(f"    {i}. {class_name}: {prob.item()*100:.2f}%")
+    
+    print(f"\n  ⚠ Note: Model is randomly initialized, so predictions are random")
+    print(f"    Load a trained checkpoint to get meaningful predictions")
+    
+except Exception as e:
+    print(f"  ⚠ Could not test with sample image: {e}")
+    print(f"    This is normal if you don't have internet connection")
+
+# Test 4: Check ImageNet classes
+print("\n✓ Test 4: ImageNet Classes")
+print(f"  - Total classes defined: {len(IMAGENET_CLASSES)}")
+print(f"  - Expected: 1000 classes")
+if len(IMAGENET_CLASSES) >= 1000:
+    print(f"  ✓ Class definitions available")
+    print(f"  - Sample classes:")
+    for idx in [0, 285, 341, 388, 980]:
+        if str(idx) in IMAGENET_CLASSES:
+            print(f"    {idx}: {IMAGENET_CLASSES[str(idx)]}")
+else:
+    print(f"  ⚠ Warning: Only {len(IMAGENET_CLASSES)} classes defined")
+
+# Test 5: Model layers
+print("\n✓ Test 5: Model Structure")
+print(f"  - Layer 1 blocks: {len(model.layer1)}")
+print(f"  - Layer 2 blocks: {len(model.layer2)}")
+print(f"  - Layer 3 blocks: {len(model.layer3)}")
+print(f"  - Layer 4 blocks: {len(model.layer4)}")
+expected_blocks = [3, 4, 6, 3]
+actual_blocks = [len(model.layer1), len(model.layer2), len(model.layer3), len(model.layer4)]
+if actual_blocks == expected_blocks:
+    print(f"  ✓ ResNet-50 architecture confirmed: {actual_blocks}")
+else:
+    print(f"  ⚠ Warning: Expected {expected_blocks}, got {actual_blocks}")
+
+print("\n" + "=" * 60)
+print("✓ All tests completed!")
+print("=" * 60)
+print("\nNext steps:")
+print("1. Train your model using the training code from:")
+print("   https://github.com/arghyaiitb/assignment_9")
+print("2. Save the best checkpoint as 'best_model.pt'")
+print("3. Place the checkpoint in this directory")
+print("4. Run: python app.py")
+print("5. Upload to Hugging Face Spaces")
+print("=" * 60)
+