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app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from PIL import Image
+
+
+def blur_score_from_pil(pil_img: Image.Image) -> float:
+    # Convert PIL -> OpenCV grayscale
+    img = np.array(pil_img.convert("RGB"))
+    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+    return float(cv2.Laplacian(gray, cv2.CV_64F).var())
+
+
+def check_blur(image: Image.Image, blur_threshold: float = 100.0):
+    if image is None:
+        return None, "No image provided."
+
+    score = blur_score_from_pil(image)
+
+    if score < blur_threshold:
+        return score, "🚫 Blurry image detected. Please re-upload a clearer image."
+    else:
+        return score, "✅ Image looks clear. Proceeding to next step."
+
+
+demo = gr.Interface(
+    fn=check_blur,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Slider(0, 500, value=100, step=1, label="Blur Threshold (Laplacian Variance)"),
+    ],
+    outputs=[
+        gr.Number(label="Blur Score (Laplacian Variance)"),
+        gr.Textbox(label="Result"),
+    ],
+    title="Image Blur Checker",
+    description="Checks image blur using variance of the Laplacian. Lower score = blurrier image.",
+)
+
+demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True)

requirements.txt

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+gradio
+opencv-python-headless
+pillow
+numpy