Update app.py

app.py

@@ -239,7 +239,6 @@ def generate_30(
     num_inference_steps: int = 125,
     randomize_seed: bool = False,
     use_resolution_binning: bool = True, 
-    num_images: int = 1,  
     juggernaut: bool = False,
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
@@ -255,7 +254,7 @@ def generate_30(
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
     options = {
-        "prompt": [prompt] * num_images,
+        "prompt": [prompt],
         "negative_prompt": [negative_prompt],
         "negative_prompt_2": [neg_prompt_2],
         "strength": denoise,
@@ -273,16 +272,12 @@ def generate_30(
     pipe.scheduler.set_timesteps(num_inference_steps,device)
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise)
-    for i in range(0, num_images, BATCH_SIZE):
-        batch_options = options.copy()
-        batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
-        if "negative_prompt" in batch_options:
-            batch_options["negative_prompt"] = options["negative_prompt"][i:i+BATCH_SIZE]
-        images.extend(pipe(**batch_options).images)
+    batch_options = options.copy()
+    rv_image = images.extend(pipe(**batch_options).images[0])
     sd_image_path = f"rv50_B_{seed}.png"
-    images[0].save(sd_image_path,optimize=False,compress_level=0)
+    rv_image.save(sd_image_path,optimize=False,compress_level=0)
     upload_to_ftp(sd_image_path)    
-    image_paths = [save_image(img) for img in images]
+    image_paths = save_image(rv_image)
     torch.cuda.empty_cache()
     gc.collect()
     return image_paths, seed
@@ -301,7 +296,6 @@ def generate_60(
     num_inference_steps: int = 250,
     randomize_seed: bool = False,
     use_resolution_binning: bool = True, 
-    num_images: int = 1,  
     juggernaut: bool = False,
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
@@ -317,7 +311,7 @@ def generate_60(
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
     options = {
-        "prompt": [prompt] * num_images,
+        "prompt": [prompt],
         "negative_prompt": [negative_prompt],
         "negative_prompt_2": [neg_prompt_2],
         "strength": denoise,
@@ -335,20 +329,16 @@ def generate_60(
     pipe.scheduler.set_timesteps(num_inference_steps,device)
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise)
-    for i in range(0, num_images, BATCH_SIZE):
-        batch_options = options.copy()
-        batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
-        if "negative_prompt" in batch_options:
-            batch_options["negative_prompt"] = options["negative_prompt"][i:i+BATCH_SIZE]
-        images.extend(pipe(**batch_options).images)
+    batch_options = options.copy()
+    rv_image = images.extend(pipe(**batch_options).images[0])
     sd_image_path = f"rv50_B_{seed}.png"
-    images[0].save(sd_image_path,optimize=False,compress_level=0)
+    rv_image.save(sd_image_path,optimize=False,compress_level=0)
     upload_to_ftp(sd_image_path)    
-    image_paths = [save_image(img) for img in images]
+    image_paths = save_image(rv_image)
     torch.cuda.empty_cache()
     gc.collect()
     return image_paths, seed
-
+    
 @spaces.GPU(duration=90)
 def generate_90(
     model_choice: str,
@@ -363,7 +353,6 @@ def generate_90(
     num_inference_steps: int = 250,
     randomize_seed: bool = False,
     use_resolution_binning: bool = True, 
-    num_images: int = 1,  
     juggernaut: bool = False,
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
@@ -379,7 +368,7 @@ def generate_90(
     generator = torch.Generator(device='cuda').manual_seed(seed)
     #prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
     options = {
-        "prompt": [prompt] * num_images,
+        "prompt": [prompt],
         "negative_prompt": [negative_prompt],
         "negative_prompt_2": [neg_prompt_2],
         "strength": denoise,
@@ -397,16 +386,12 @@ def generate_90(
     pipe.scheduler.set_timesteps(num_inference_steps,device)
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise)
-    for i in range(0, num_images, BATCH_SIZE):
-        batch_options = options.copy()
-        batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
-        if "negative_prompt" in batch_options:
-            batch_options["negative_prompt"] = options["negative_prompt"][i:i+BATCH_SIZE]
-        images.extend(pipe(**batch_options).images)
+    batch_options = options.copy()
+    rv_image = images.extend(pipe(**batch_options).images[0])
     sd_image_path = f"rv50_B_{seed}.png"
-    images[0].save(sd_image_path,optimize=False,compress_level=0)
+    rv_image.save(sd_image_path,optimize=False,compress_level=0)
     upload_to_ftp(sd_image_path)    
-    image_paths = [save_image(img) for img in images]
+    image_paths = save_image(rv_image)
     torch.cuda.empty_cache()
     gc.collect()
     return image_paths, seed
@@ -469,13 +454,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             value=DEFAULT_STYLE_NAME,
             label="Quality Style",
         )
-        num_images = gr.Slider(
-            label="Number of Images",
-            minimum=1,
-            maximum=5,
-            step=1,
-            value=1,
-        )
         with gr.Row():
             with gr.Column(scale=1):
                 use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True)
@@ -565,7 +543,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             guidance_scale,
             num_inference_steps,
             randomize_seed, 
-            num_images,
             juggernaut,
             denoise
         ],
@@ -590,7 +567,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             guidance_scale,
             num_inference_steps,
             randomize_seed, 
-            num_images,
             juggernaut,
             denoise
         ],
@@ -615,7 +591,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             guidance_scale,
             num_inference_steps,
             randomize_seed, 
-            num_images,
             juggernaut,
             denoise
         ],