Create app.py

app.py

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+import gradio as gr
+import torch
+from model import CNNLSTMClassifier
+from utils import extract_frames
+
+model = CNNLSTMClassifier()
+model.load_state_dict(torch.load("lbw_classifier.pt", map_location='cpu'))
+model.eval()
+
+classes = ["Not LBW", "LBW"]
+
+def predict(video):
+    frames = extract_frames(video)
+    with torch.no_grad():
+        output = model(frames)
+        pred = torch.argmax(output, dim=1).item()
+        prob = torch.softmax(output, dim=1)[0][pred].item()
+    return f"Prediction: {classes[pred]} (Confidence: {prob:.2%})"
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Video(type="filepath"),
+    outputs=gr.Text(),
+    title="Smart LBW Classifier",
+    description="Upload a cricket video. The AI model will predict whether it's an LBW or not."
+)
+
+iface.launch()