Update app_v4.py

app_v4.py

@@ -67,33 +67,6 @@ def resize_image_to_max_side(image: Image, max_side_length=1024) -> Image:
     resized_image = image.resize(new_size, Image.BILINEAR)
     return resized_image
 
-@spaces.GPU(duration=6, progress=gr.Progress(track_tqdm=True))
-@torch.no_grad()
-def generate_image(prompt, scale, steps, control_image, controlnet_conditioning_scale, guidance_scale, seed, guidance_end):
-    generator = torch.Generator().manual_seed(seed)
-    # Load control image
-    control_image = load_image(control_image)
-    w, h = control_image.size
-    w = w - w % 32
-    h = h - h % 32
-    control_image = control_image.resize((int(w * scale), int(h * scale)), resample=2)  # Resample.BILINEAR
-    print("Size to: " + str(control_image.size[0]) + ", " + str(control_image.size[1]))
-    print(f"PromptLog: {repr(prompt)}")
-    with torch.inference_mode():
-        image = pipe(
-            generator=generator,
-            prompt=prompt,
-            control_image=control_image,
-            controlnet_conditioning_scale=controlnet_conditioning_scale,
-            num_inference_steps=steps,
-            guidance_scale=guidance_scale,
-            height=control_image.size[1],
-            width=control_image.size[0],
-            control_guidance_start=0.0,
-            control_guidance_end=guidance_end,
-        ).images[0]
-        # print("Type: " + str(type(image)))
-    return image
 
 def combine_caption_focus(caption, focus):
     try:
@@ -173,11 +146,10 @@ def generate_image(prompt, scale, steps, control_image, controlnet_conditioning_
         ).images[0]
         # print("Type: " + str(type(image)))
     return image
-progress = gr.Progress(track_tqdm=True)
 
 def process_image(control_image, user_prompt, system_prompt, scale, steps, 
                 controlnet_conditioning_scale, guidance_scale, seed, 
-                guidance_end, temperature, top_p, max_new_tokens, log_prompt, progress):
+                guidance_end, temperature, top_p, max_new_tokens, log_prompt, progress = gr.Progress(track_tqdm=True)):
     # Initialize with empty caption
     final_prompt = user_prompt.strip()
     # If no user prompt provided, generate a caption first