Initial Commit

app.py

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+import gradio as gr
+import timm
+
+model = timm.create_model("MobileOne_s2", pretrained = False)
+model.head.fc = nn.Linear(model.head.fc.in_features,3)
+model.load_state_dict(torch.load("olive_classifier.pth", weights_only=True))
+model.eval()
+
+categories = ("Aculus Olearius", "Healthy", "Peacock Spot")
+
+
+def classify_health(input_img):
+    probs = model(input_img)
+    idx = probs.argmax()
+    return dict(zip(categories, map(float, probs)))
+
+
+labels = gr.Label()
+examples = [
+    "examples/healthy.jpg",
+    "examples/aculus_2.jpg",
+    "examples/peacock_3.jpeg",
+]
+demo = gr.Interface(
+    classify_health,
+    inputs=gr.Image(height=224, width=224),
+    outputs=labels,
+    examples=examples,
+)
+demo.launch(inline=False)

olive-classifier.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:25c66a2ae9d983f1f2d21fbd9a76637991541b821a78dbd5db5879aa521b32ce
+size 23940298

requirements.txt

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+gradio==4.43.0
+torchvision==0.19.0
+timm==1.0.9
+torch==2.4.0