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app.py

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+import torch
+import torch.nn as nn
+from torchvision import models, transforms
+from PIL import Image
+import gradio as gr
+
+DEVICE = torch.device("cpu")
+NUM_CLASSES = 64
+MODEL_PATH = "resnet18_animals_64.pth"
+CLASS_NAMES_FILE = "classes.txt"
+
+with open(CLASS_NAMES_FILE, "r") as f:
+    class_names = [line.strip() for line in f.readlines()]
+
+def load_model():
+    model = models.resnet18(weights=None)
+    num_ftrs = model.fc.in_features
+    model.fc = nn.Linear(num_ftrs, NUM_CLASSES)
+    
+    model.load_state_dict(torch.load(MODEL_PATH, map_location=DEVICE))
+    model.to(DEVICE)
+    model.eval()
+    return model
+
+model = load_model()
+
+image_transforms = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+    transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+])
+
+def predict(image):
+    img_tensor = image_transforms(image).unsqueeze(0)
+    img_tensor = img_tensor.to(DEVICE)
+    
+    with torch.no_grad():
+        outputs = model(img_tensor)
+        probabilities = torch.nn.functional.softmax(outputs[0], dim=0)
+    
+    top3_prob, top3_catid = torch.topk(probabilities, 3)
+    
+    confidences = {}
+    for i in range(top3_prob.size(0)):
+        confidences[class_names[top3_catid[i]]] = float(top3_prob[i])
+    
+    return confidences
+
+title = "Animal Classifier 🐾"
+description = "Nhận diện 64 loài động vật sử dụng mô hình ResNet-18."
+examples = []
+
+interface = gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(type="pil"), 
+    outputs=gr.Label(num_top_classes=3),
+    title=title,
+    description=description
+)
+
+if __name__ == "__main__":
+    interface.launch()

classes.txt

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+antelope
+bear
+beaver
+bee
+bison
+blackbird
+buffalo
+butterfly
+camel
+cat
+cheetah
+chimpanzee
+chinchilla
+cow
+crab
+crocodile
+deer
+dog
+dolphin
+donkey
+duck
+eagle
+elephant
+falcon
+ferret
+flamingo
+fox
+frog
+giraffe
+goat
+goose
+gorilla
+grasshopper
+hawk
+hedgehog
+hippopotamus
+hyena
+iguana
+jaguar
+kangaroo
+koala
+lemur
+leopard
+lizard
+lynx
+mole
+mongoose
+ostrich
+otter
+owl
+panda
+peacock
+penguin
+porcupine
+raccoon
+seal
+sheep
+snail
+snake
+spider
+squid
+walrus
+whale
+wolf

requirements.txt

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+torch
+torchvision
+gradio

resnet18_animals_64.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1c88225be3e5fe736a5d23aac1bae057916d021f030cd4baec58e012296bcc12
+size 44918155