Upload app.py

app.py

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+import cv2
+import numpy as np
+import gradio as gr
+import tempfile
+
+def color_transfer(source, target):
+    # Resize target to match source
+    target = cv2.resize(target, (source.shape[1], source.shape[0]))
+
+    # Convert to LAB color space
+    source_lab = cv2.cvtColor(source, cv2.COLOR_BGR2LAB).astype("float32")
+    target_lab = cv2.cvtColor(target, cv2.COLOR_BGR2LAB).astype("float32")
+
+    # Calculate mean and std dev
+    (l_mean_src, a_mean_src, b_mean_src), (l_std_src, a_std_src, b_std_src) = cv2.meanStdDev(source_lab)
+    (l_mean_tar, a_mean_tar, b_mean_tar), (l_std_tar, a_std_tar, b_std_tar) = cv2.meanStdDev(target_lab)
+
+    # Apply color transfer
+    l, a, b = cv2.split(source_lab)
+    l -= l_mean_src[0]
+    a -= a_mean_src[0]
+    b -= b_mean_src[0]
+    l = (l * (l_std_tar[0] / l_std_src[0])) + l_mean_tar[0]
+    a = (a * (a_std_tar[0] / a_std_src[0])) + a_mean_tar[0]
+    b = (b * (b_std_tar[0] / b_std_src[0])) + b_mean_tar[0]
+
+    # Merge and convert back to BGR
+    transfer_lab = cv2.merge([l, a, b])
+    transfer_lab = np.clip(transfer_lab, 0, 255).astype("uint8")
+    result_bgr = cv2.cvtColor(transfer_lab, cv2.COLOR_LAB2BGR)
+
+    return result_bgr, target  # Return resized target too
+
+def process_images(source_img, ref_img, red_scale, green_scale, blue_scale, brightness, contrast):
+    if source_img is None or ref_img is None:
+        raise gr.Error("Please upload both the source image and the reference image before clicking Convert.")
+
+    # Convert RGB to BGR
+    source_bgr = cv2.cvtColor(source_img, cv2.COLOR_RGB2BGR)
+    ref_bgr = cv2.cvtColor(ref_img, cv2.COLOR_RGB2BGR)
+
+    # Perform color transfer
+    output_bgr, resized_ref_bgr = color_transfer(source_bgr, ref_bgr)
+
+    # Apply color scaling
+    b, g, r = cv2.split(output_bgr)
+    r = np.clip(r * red_scale, 0, 255).astype(np.uint8)
+    g = np.clip(g * green_scale, 0, 255).astype(np.uint8)
+    b = np.clip(b * blue_scale, 0, 255).astype(np.uint8)
+    output_bgr = cv2.merge([b, g, r])
+
+    # Apply brightness and contrast adjustment
+    output_bgr = cv2.convertScaleAbs(output_bgr, alpha=contrast, beta=brightness)
+
+    # Convert all images to RGB for display
+    source_rgb = cv2.cvtColor(source_bgr, cv2.COLOR_BGR2RGB)
+    ref_rgb = cv2.cvtColor(resized_ref_bgr, cv2.COLOR_BGR2RGB)
+    output_rgb = cv2.cvtColor(output_bgr, cv2.COLOR_BGR2RGB)
+
+    # Save output to temp file for download
+    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+    cv2.imwrite(temp_file.name, output_bgr)
+
+    return source_rgb, ref_rgb, output_rgb, temp_file.name
+
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 🎨 Color Transfer: Style Match Between Images")
+
+    with gr.Row():
+        source_input = gr.Image(type="numpy", label="Upload Source Image")
+        ref_input = gr.Image(type="numpy", label="Upload Reference Image")
+
+    with gr.Row():
+        red_slider = gr.Slider(0.0, 2.0, value=1.0, label="Red Scale")
+        green_slider = gr.Slider(0.0, 2.0, value=1.0, label="Green Scale")
+        blue_slider = gr.Slider(0.0, 2.0, value=1.0, label="Blue Scale")
+
+    with gr.Row():
+        brightness_slider = gr.Slider(-100, 100, value=0, label="Brightness")
+        contrast_slider = gr.Slider(0.1, 3.0, value=1.0, label="Contrast")
+
+    convert_button = gr.Button("Convert")
+
+    with gr.Row():
+        source_display = gr.Image(label="Source Image")
+        ref_display = gr.Image(label="Resized Reference Image")
+        output_display = gr.Image(label="Output Image")
+
+    download_output = gr.File(label="Download Result Image")
+
+    convert_button.click(
+        fn=process_images,
+        inputs=[
+            source_input, ref_input,
+            red_slider, green_slider, blue_slider,
+            brightness_slider, contrast_slider
+        ],
+        outputs=[source_display, ref_display, output_display, download_output]
+    )
+
+demo.launch()