Create app.py

app.py

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+import timm
+from PIL import Image
+from torchvision import transforms as T
+import gradio as gr
+import torch
+
+model = timm.create_model("hf_hub:OmAlve/swin_s3_base_224-Foods-101", pretrained=True)
+image_size = (224,224)
+
+test_tf = T.Compose([
+    T.Resize(image_size),
+    T.ToTensor(),
+    T.Normalize(
+        mean = (0.5,0.5,0.5),
+        std = (0.5,0.5,0.5)
+    )
+])
+
+labels = [
+    "apple_pie",
+    "baby_back_ribs",
+    "baklava",
+    "beef_carpaccio",
+    "beef_tartare",
+    "beet_salad",
+    "beignets",
+    "bibimbap",
+    "bread_pudding",
+    "breakfast_burrito",
+    "bruschetta",
+    "caesar_salad",
+    "cannoli",
+    "caprese_salad",
+    "carrot_cake",
+    "ceviche",
+    "cheesecake",
+    "cheese_plate",
+    "chicken_curry",
+    "chicken_quesadilla",
+    "chicken_wings",
+    "chocolate_cake",
+    "chocolate_mousse",
+    "churros",
+    "clam_chowder",
+    "club_sandwich",
+    "crab_cakes",
+    "creme_brulee",
+    "croque_madame",
+    "cup_cakes",
+    "deviled_eggs",
+    "donuts",
+    "dumplings",
+    "edamame",
+    "eggs_benedict",
+    "escargots",
+    "falafel",
+    "filet_mignon",
+    "fish_and_chips",
+    "foie_gras",
+    "french_fries",
+    "french_onion_soup",
+    "french_toast",
+    "fried_calamari",
+    "fried_rice",
+    "frozen_yogurt",
+    "garlic_bread",
+    "gnocchi",
+    "greek_salad",
+    "grilled_cheese_sandwich",
+    "grilled_salmon",
+    "guacamole",
+    "gyoza",
+    "hamburger",
+    "hot_and_sour_soup",
+    "hot_dog",
+    "huevos_rancheros",
+    "hummus",
+    "ice_cream",
+    "lasagna",
+    "lobster_bisque",
+    "lobster_roll_sandwich",
+    "macaroni_and_cheese",
+    "macarons",
+    "miso_soup",
+    "mussels",
+    "nachos",
+    "omelette",
+    "onion_rings",
+    "oysters",
+    "pad_thai",
+    "paella",
+    "pancakes",
+    "panna_cotta",
+    "peking_duck",
+    "pho",
+    "pizza",
+    "pork_chop",
+    "poutine",
+    "prime_rib",
+    "pulled_pork_sandwich",
+    "ramen",
+    "ravioli",
+    "red_velvet_cake",
+    "risotto",
+    "samosa",
+    "sashimi",
+    "scallops",
+    "seaweed_salad",
+    "shrimp_and_grits",
+    "spaghetti_bolognese",
+    "spaghetti_carbonara",
+    "spring_rolls",
+    "steak",
+    "strawberry_shortcake",
+    "sushi",
+    "tacos",
+    "takoyaki",
+    "tiramisu",
+    "tuna_tartare",
+    "waffles"
+  ]
+
+def predict(img):
+  inp = test_tf(img).unsqueeze(0)
+  with torch.no_grad():
+    predictions = torch.nn.functional.softmax(model(inp)[0], dim=0)
+    toplabels = predictions.argsort(descending=True)[:5]
+  results = {labels[label] : float(predictions[label]) for label in toplabels}
+  return results
+
+gr.Interface(fn=predict,
+             inputs=gr.Image(type="pil"),
+             outputs="label",
+             examples=['./miso soup.jpg','./cupcake.jpg','./pasta.jpg'],
+             live=True).launch()
+