YOLO acne model deployment

app.py

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+import gradio as gr
+import torch
+from PIL import Image
+
+# Load YOLOv5 custom model
+model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt')
+
+def predict(image):
+    results = model(image)
+
+    detections = results.pandas().xyxy[0]
+
+    output = []
+
+    for _, row in detections.iterrows():
+        output.append({
+            "class": row["name"],
+            "confidence": float(row["confidence"])
+        })
+
+    return output
+
+# Gradio UI (also becomes API)
+interface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs="json",
+    title="Acne YOLO Detection API"
+)
+
+interface.launch()

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8ff676000024b38ed87de6f22e9d7c0a3a099558bd8dd23fc1a537accfb6090b
+size 14416559

requirements.txt

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+gradio==4.44.1
+torch
+torchvision
+opencv-python
+numpy
+Pillow
+ultralytics