fix

app.py

@@ -59,7 +59,7 @@ colors = [
 ]
 
 color_map = {
-    color_id: f"#{hex(color[2])[2:].zfill(2)}{hex(color[1])[2:].zfill(2)}{hex(color[0])[2:].zfill(2)}" for color_id, color in enumerate(colors)
+    f"{color_id}": f"#{hex(color[2])[2:].zfill(2)}{hex(color[1])[2:].zfill(2)}{hex(color[0])[2:].zfill(2)}" for color_id, color in enumerate(colors)
 }
 
 def run_clip_dinoiser(input_image, text_prompts):
@@ -80,21 +80,6 @@ def run_clip_dinoiser(input_image, text_prompts):
     output = output[0].argmax(dim=0)
     mask = mask2rgb(output, palette)
 
-    # fig = plt.figure(figsize=(3, 1))
-    # classes = np.unique(output).tolist()
-    # plt.imshow(np.array(itemgetter(*classes)(palette)).reshape(1, -1, 3))
-    # plt.xticks(np.arange(len(classes)), list(itemgetter(*classes)(text_prompts)), rotation=45)
-    # plt.yticks([])
-
-    
-    # fig, ax = plt.subplots(nrows=1, ncols=2)
-    # alpha=0.5
-    # blend = (alpha)*np.array(image)/255. + (1-alpha) * mask/255.
-    # ax[0].imshow(blend)
-    # ax[1].imshow(mask)
-    # ax[0].axis('off')
-    # ax[1].axis('off')
-
     classes = np.unique(output).tolist()
     palette_array = np.array(itemgetter(*classes)(palette)).reshape(1, -1, 3)
     alpha=0.5
@@ -102,7 +87,7 @@ def run_clip_dinoiser(input_image, text_prompts):
 
     h_text = list()
     for idx, text in enumerate(text_prompts):
-        h_text.append((text, idx))
+        h_text.append((text, f"{idx}"))
     return blend, mask, h_text
 
 
@@ -116,7 +101,7 @@ if __name__ == "__main__":
 
         with gr.Row():
             with gr.Column():
-                input_image = gr.Image(type="pil")
+                input_image = gr.Image(type="pil", label="Input Image")
                 text_prompts = gr.Textbox(label="Enter comma-separated prompts")
                 run_button = gr.Button(value="Run")
 
@@ -124,12 +109,14 @@ if __name__ == "__main__":
                 with gr.Row():
                     overlay_mask = gr.Image(
                         type="numpy",
+                        label="Overlay Mask",
                     )
                     only_mask = gr.Image(
                         type="numpy",
+                        label="Segmentation Mask"
                     )
                 h_text = gr.HighlightedText(
-                    label="text",
+                    label="Labels",
                     combine_adjacent=False,
                     show_legend=False,
                     color_map=color_map