App

app.py

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+import gradio as gr
+import cv2, numpy as np
+from PIL import Image
+
+# -------------------------------------------------
+# 🔧 CORE FUNCTION
+# -------------------------------------------------
+def remove_folds(image, intensity=0.5):
+    if image is None:
+        return None
+
+    img = np.array(image.convert("RGB"))
+    img_lab = cv2.cvtColor(img, cv2.COLOR_RGB2LAB)
+    l, a, b = cv2.split(img_lab)
+
+    # --- (1) Smooth illumination correction ---
+    ksize = int(49 + intensity * 100)  # kernel size changes with intensity
+    ksize = ksize + 1 if ksize % 2 == 0 else ksize  # must be odd
+    l_blur = cv2.GaussianBlur(l, (ksize, ksize), 0)
+    l_equal = cv2.divide(l, l_blur, scale=128)
+
+    # --- (2) Frequency-domain smoothing ---
+    freq = np.fft.fft2(l_equal)
+    freqshift = np.fft.fftshift(freq)
+    rows, cols = l_equal.shape
+    crow, ccol = rows // 2, cols // 2
+    mask = np.ones((rows, cols), np.uint8)
+    r = int(10 + intensity * 30)  # notch size grows with intensity
+    mask[crow - r:crow + r, ccol - r:ccol + r] = 0
+    freqshift = freqshift * mask
+    ishift = np.fft.ifftshift(freqshift)
+    l_flat = np.abs(np.fft.ifft2(ishift))
+    l_flat = cv2.normalize(l_flat, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)
+
+    # --- (3) Merge back and convert ---
+    img_lab = cv2.merge([l_flat, a, b])
+    result = cv2.cvtColor(img_lab, cv2.COLOR_LAB2RGB)
+    return Image.fromarray(result)
+
+# -------------------------------------------------
+# 🎛️ GRADIO UI
+# -------------------------------------------------
+title = "🪄 Saree Fold Remover (Lighting Only, No Distortion)"
+description = """
+Upload a flat saree or fabric image.<br>
+Adjust the **Fold Intensity** slider — higher values remove deeper folds.<br>
+The process equalizes lighting only, keeping weave and motifs intact.
+"""
+
+iface = gr.Interface(
+    fn=remove_folds,
+    inputs=[
+        gr.Image(label="Upload Saree Image", type="pil"),
+        gr.Slider(
+            0.0,
+            1.0,
+            value=0.5,
+            step=0.05,
+            label="Fold Intensity",
+            info="Higher = stronger flattening (lighting only)",
+            interactive=True
+        ),
+    ],
+    outputs=gr.Image(label="Flat, Fold-Free Output"),
+    title=title,
+    description=description,
+    live=False,        # prevents rerun while moving
+    throttle=0.8       # waits 0.8 s before triggering
+)
+
+if __name__ == "__main__":
+    iface.launch()