change output format

app.py

@@ -13,19 +13,21 @@ COLOR_NAME = ['black', 'brown', 'blue', 'gray', 'green', 'orange', 'pink', 'purp
 
 def get_top_names(img):
     # resize images to smaller size
-    anchor = 512
+    anchor = 256
     width = img.shape[1]
     height = img.shape[0]
-    if width > 1024 or height > 1024:
+    if width > 512 or height > 512:
         if width >= height:
             dim = (np.floor(width/height*anchor).astype(int), anchor)
         else:
             dim = (anchor, np.floor(height/width*anchor).astype(int))
         img = cv2.resize(img, dim, interpolation=cv2.INTER_LINEAR)
 
+    # obtain color names of all the pixels
     w2c = np.load('w2c11_j.npy').astype(np.float16)
     _, _, name_idx_img, _ = im2c(img, w2c)
 
+    # compute the order of each name based on the numbers of each name
     filtered_counts = Counter(name_idx_img[name_idx_img <= 10])
     sorted_counts = sorted(filtered_counts.items(), key=lambda x: x[1], reverse=True)
     top_3_values = [num for num, count in sorted_counts[:3]]
@@ -42,7 +44,7 @@ def classify_and_log(images):
     for folder in category_folders.values():
         os.makedirs(folder, exist_ok=True)
 
-    log_file = os.path.join(output_folder, "log.txt")
+    log_file = os.path.join(output_folder, "top3colors.txt")
     
     results = {i: [] for i in range(11)}
 
@@ -60,7 +62,7 @@ def classify_and_log(images):
 
             print(f"Image:{filename} -> Top 3 colors:{category}\n")
 
-            log.write(f"{filename} -> {category}\n")
+            log.write(f"{filename} -> 1 {category[0]}, 2 {category[1]}, 3 {category[2]}\n")
 
             results[cat_id[0]].append(target_path)
 
@@ -87,7 +89,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             image_input = gr.File(
-                        label="Drag (Select) more than one photos",
+                        label="Drag/Select more than one images",
                         file_types=["image"],
                         file_count="multiple"
                     )
@@ -106,7 +108,7 @@ with gr.Blocks() as demo:
     # with gr.Row():
     #     image_output = {str(i): gr.Gallery(label=f"{i}") for i in range(11)}
     
-    log_output = gr.File(label="download logs")
+    log_output = gr.File(label="download results")
 
     classify_btn.click(
         classify_and_log, 

naming.py

@@ -72,8 +72,3 @@ if __name__ == "__main__":
 
     cv2.imwrite('colormap_j.jpg', cv2.cvtColor(color_img, cv2.COLOR_BGR2RGB))
 
-    # print(prob_map.sum(axis=2))
-    # print(name_idx_img)
-    # print(max_prob_img.shape)
-    # print(color_img)
-