Add app.py

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+import numpy as np
+
+with gr.Blocks() as demo:
+    tolerance = gr.Slider(label="Tolerance",
+                          info="How different colors can be in a segment.",
+                          minimum=0, maximum=256 * 3, value=50)
+    with gr.Row():
+        input_img = gr.Image(label="Input")
+        output_img = gr.Image(label="Selected Segment")
+
+
+    def get_select_coords(img, tolerance, evt: gr.SelectData):
+        visited_pixels = set()
+        pixels_in_queue = set()
+        pixels_in_segment = set()
+        start_pixel = img[evt.index[1], evt.index[0]]
+        pixels_in_queue.add((evt.index[1], evt.index[0]))
+        while len(pixels_in_queue) > 0:
+            pixel = pixels_in_queue.pop()
+            visited_pixels.add(pixel)
+            neighbors = []
+            if pixel[0] > 0:
+                neighbors.append((pixel[0] - 1, pixel[1]))
+            if pixel[0] < img.shape[0] - 1:
+                neighbors.append((pixel[0] + 1, pixel[1]))
+            if pixel[1] > 0:
+                neighbors.append((pixel[0], pixel[1] - 1))
+            if pixel[1] < img.shape[1] - 1:
+                neighbors.append((pixel[0], pixel[1] + 1))
+            for neighbor in neighbors:
+                if neighbor in visited_pixels:
+                    continue
+                neighbor_pixel = img[neighbor[0], neighbor[1]]
+                if np.abs(neighbor_pixel - start_pixel).sum() < tolerance:
+                    pixels_in_queue.add(neighbor)
+                    pixels_in_segment.add(neighbor)
+
+        out = img.copy() * 0.2
+        out = out.astype(np.uint8)
+        for pixel in pixels_in_segment:
+            out[pixel[0], pixel[1]] = img[pixel[0], pixel[1]]
+        return out
+
+
+    input_img.select(get_select_coords, [input_img, tolerance], output_img)
+
+if __name__ == "__main__":
+    demo.launch()