Update app.py

app.py

@@ -533,12 +533,20 @@ def generate_video(image, prompt, max_tokens):
     # Dùng multiprocessing
     # with multiprocessing.Pool(processes=20) as pool:
     # with ProcessPoolExecutor(max_workers=20) as pool:
-    ctx = multiprocessing.get_context()
-    ctx.Process(target=lambda: None).daemon = False
-    with ctx.Pool(processes=20) as pool:
-        text_imgs = pool.map(generate_text_img_wrapper, params_for_text)
-        hidden_imgs = pool.map(generate_hidden_img_wrapper, params_for_hidden)
-
+    # ctx = multiprocessing.get_context()
+    # ctx.Process(target=lambda: None).daemon = False
+    # with ctx.Pool(processes=20) as pool:
+    #     text_imgs = pool.map(generate_text_img_wrapper, params_for_text)
+    #     hidden_imgs = pool.map(generate_hidden_img_wrapper, params_for_hidden)
+    text_imgs = []
+    for param in tqdm.tqdm(params_for_text):
+        result = generate_text_img_wrapper(param)
+        text_imgs.append(result)
+    hidden_imgs = []
+    for param in tqdm.tqdm(params_for_hidden):
+        result = generate_hidden_img_wrapper(param)
+        hidden_imgs.append(result)
+        
     for i in range(len(text_imgs)):
         overlay = heatmap_imgs[i]
         text_img = text_imgs[i]
@@ -575,7 +583,7 @@ with gr.Blocks() as demo:
         with gr.Column():
             image = gr.Image(label="Upload your image", type = 'filepath')
             prompt = gr.Textbox(label="Describe your prompt", value="List all the text." )
-            max_tokens = gr.Slider(label="Max token output (⚠️ Choose <100 for faster response)", minimum=1, maximum=512, value=50)
+            max_tokens = gr.Slider(label="Max token output (⚠️ Choose <100 for faster response)", minimum=1, maximum=256, value=50)
             btn = gr.Button("Inference")
         video = gr.Video(label="Visualization Video")