Create app.py

app.py

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+import gradio as gr
+from ultralytics import YOLO
+import cv2
+from PIL import Image
+import numpy as np
+
+# Load model
+MODEL_PATH = "Best_Model1.pt"
+model = YOLO(MODEL_PATH)
+
+def detect_flash_gradio(image: Image.Image):
+    # Convert PIL image to OpenCV format
+    image_cv = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+
+    # Run detection
+    results = model(image_cv)
+
+    # Extract detection info
+    detections = results[0].boxes.data.tolist()
+    num_detections = len(detections)
+
+    message = ""
+    if num_detections > 0:
+        message += f"Flash(es) Detected: {num_detections}\n"
+        for i, det in enumerate(detections):
+            x1, y1, x2, y2, conf, cls = det
+            message += f"  Flash {i+1}: Confidence={conf:.2f}, Position=[{int(x1)},{int(y1)},{int(x2)},{int(y2)}]\n"
+    else:
+        message = "No Flash Detected."
+
+    # Plot result
+    res_plotted = results[0].plot()
+    res_rgb = cv2.cvtColor(res_plotted, cv2.COLOR_BGR2RGB)
+    output_image = Image.fromarray(res_rgb)
+
+    return output_image, message
+
+# Interface with tabs: Upload or Webcam
+with gr.Blocks() as demo:
+    gr.Markdown("Flash Detection")
+    gr.Markdown("Upload an image or use your webcam to detect flash.")
+
+    with gr.Tab("Upload Image"):
+        upload_input = gr.Image(type="pil", label="Upload Image")
+        upload_btn = gr.Button("Detect Flash")
+        upload_output_img = gr.Image(type="pil", label="Detected Image")
+        upload_output_text = gr.Textbox(label="Detection Info")
+
+    with gr.Tab("Use Webcam"):
+        webcam_input = gr.Image(source="webcam", type="pil", label="Capture from Webcam")
+        webcam_btn = gr.Button("Detect Flash")
+        webcam_output_img = gr.Image(type="pil", label="Detected Image")
+        webcam_output_text = gr.Textbox(label="Detection Info")
+
+    upload_btn.click(fn=detect_flash_gradio, inputs=upload_input, outputs=[upload_output_img, upload_output_text])
+    webcam_btn.click(fn=detect_flash_gradio, inputs=webcam_input, outputs=[webcam_output_img, webcam_output_text])
+
+demo.launch()