Update app.py

app.py

@@ -1,27 +1,27 @@
+import os
+import random
+import uuid
 import gradio as gr
-import spaces
 import numpy as np
-import random
-from diffusers import DiffusionPipeline
-import torch
 from PIL import Image
+import torch
+from diffusers import DiffusionPipeline
+import spaces
 
+# Setup
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model_repo_id = "stabilityai/stable-diffusion-3.5-large-turbo"
-
 torch_dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
 
 pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
 pipe = pipe.to(device)
-
 pipe.load_lora_weights("strangerzonehf/SD3.5-Turbo-Portrait-LoRA", weight_name="SD3.5-Turbo-Portrait.safetensors")
-trigger_word = "Turbo Portrait"  
 pipe.fuse_lora(lora_scale=1.0)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
-# Define styles
+# Style presets
 style_list = [
     {
         "name": "3840 x 2160",
@@ -45,178 +45,125 @@ style_list = [
     },
 ]
 
-STYLE_NAMES = [style["name"] for style in style_list]
-DEFAULT_STYLE_NAME = STYLE_NAMES[0]
+STYLE_NAMES = [s["name"] for s in style_list]
 
-grid_sizes = {
-    "2x1": (2, 1),
-    "1x2": (1, 2),
-    "2x2": (2, 2),
-    "2x3": (2, 3),
-    "3x2": (3, 2),
-    "1x1": (1, 1)
-}
+def randomize_seed_fn(seed, randomize):
+    return random.randint(0, MAX_SEED) if randomize else seed
+
+def save_image(img):
+    filename = str(uuid.uuid4()) + ".png"
+    img.save(filename)
+    return filename
 
 @spaces.GPU(duration=60)
-def infer(
+def generate_images(
     prompt,
-    negative_prompt="",
-    seed=42,
-    randomize_seed=False,
-    width=1024,
-    height=1024,
-    guidance_scale=7.5,
-    num_inference_steps=10,
-    style="Style Zero",
-    grid_size="1x1",
-    progress=gr.Progress(track_tqdm=True),
+    style,
+    negative_prompt,
+    seed,
+    randomize_seed,
+    width,
+    height,
+    guidance_scale,
+    num_inference_steps,
+    num_images,
+    progress=gr.Progress(track_tqdm=True)
 ):
+    seed = randomize_seed_fn(seed, randomize_seed)
+    generator = torch.Generator(device=device).manual_seed(seed)
+
     selected_style = next(s for s in style_list if s["name"] == style)
     styled_prompt = selected_style["prompt"].format(prompt=prompt)
-    styled_negative_prompt = selected_style["negative_prompt"]
-
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-
-    generator = torch.Generator().manual_seed(seed)
-
-    grid_size_x, grid_size_y = grid_sizes.get(grid_size, (1, 1))
-    num_images = grid_size_x * grid_size_y
-
-    options = {
-        "prompt": styled_prompt,
-        "negative_prompt": styled_negative_prompt,
-        "guidance_scale": guidance_scale,
-        "num_inference_steps": num_inference_steps,
-        "width": width,
-        "height": height,
-        "generator": generator,
-        "num_images_per_prompt": num_images,
-    }
-
-    torch.cuda.empty_cache()  # Clear GPU memory
-    result = pipe(**options)
-
-    grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
-
-    for i, img in enumerate(result.images[:num_images]):
-        grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
-
-    return grid_img, seed
-
-examples = [
-    "A tiny astronaut hatching from an egg on the moon, 4k, planet theme",
-    "An anime-style illustration of a delicious, golden-brown wiener schnitzel on a plate, served with fresh lemon slices, parsley --style raw5",
-    "Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
-    "A cat holding a sign that says hello world --ar 85:128 --v 6.0 --style raw"
-]
-
+    styled_negative_prompt = selected_style["negative_prompt"] if not negative_prompt else negative_prompt
+
+    images = []
+    for _ in range(num_images):
+        image = pipe(
+            prompt=styled_prompt,
+            negative_prompt=styled_negative_prompt,
+            width=width,
+            height=height,
+            guidance_scale=guidance_scale,
+            num_inference_steps=num_inference_steps,
+            generator=generator
+        ).images[0]
+        images.append(image)
+
+    image_paths = [save_image(img) for img in images]
+    return image_paths, seed
+
+# CSS & Interface
 css = '''
-.gradio-container{max-width: 585px !important}
-h1{text-align:center}
-footer {
-    visibility: hidden
+.gradio-container {
+    max-width: 150%;
+    margin: 0 auto;
 }
+h1 { text-align: center; }
+footer { visibility: hidden; }
 '''
 
-with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown("## SD3.5 Turbo Portrait")
-
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-
-            run_button = gr.Button("Run", scale=0, variant="primary")
-
-        result = gr.Image(label="Result", show_label=False)
-
-
-        with gr.Row(visible=True):
-            grid_size_selection = gr.Dropdown(
-                choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
-                value="1x1",
-                label="Grid Size"
-            )
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
-                visible=False,
-            )
-
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
+examples = [
+    "portrait photo of a futuristic astronaut",
+    "macro shot of a water droplet on a leaf",
+    "hyper-realistic food photography of a burger",
+    "cyberpunk city at night, rain, neon lights",
+    "ultra detailed fantasy landscape with dragons",
+]
 
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+with gr.Blocks(css=css, theme="YTheme/GMaterial") as demo:
+    gr.Markdown("## SD3.5 Turbo: Text to Image [10-Images]")
 
+    with gr.Row():
+        with gr.Column(scale=1):
             with gr.Row():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=512,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=512,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,
+                prompt = gr.Text(
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
                 )
+                run_button = gr.Button("Run", scale=0, variant="primary")
 
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=7.5,
-                    step=0.1,
-                    value=0.0,
-                )
+            result_gallery = gr.Gallery(show_label=False, format="png", columns=2, object_fit="contain")
 
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
+            with gr.Accordion("Advanced Settings", open=False):
+                num_images = gr.Slider(
+                    label="Number of Images",
                     minimum=1,
-                    maximum=50,
+                    maximum=10,
+                    value=5,
                     step=1,
-                    value=8,
-                )       
-                
-                style_selection = gr.Radio(
-                    show_label=True,
-                    container=True,
-                    interactive=True,
-                    choices=STYLE_NAMES,
-                    value=DEFAULT_STYLE_NAME,
-                    label="Quality Style",
                 )
+                style = gr.Dropdown(label="Select Style", choices=STYLE_NAMES, value=STYLE_NAMES[0])
 
-        gr.Examples(examples=examples, 
-                    inputs=[prompt], 
-                    outputs=[result, seed], 
-                    fn=infer, 
-                    cache_examples=False)
+                negative_prompt = gr.Text(
+                    label="Negative Prompt",
+                    max_lines=4,
+                    lines=3,
+                    value="cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly"
+                )
+                seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
+                randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+                with gr.Row():
+                    width = gr.Slider(label="Width", minimum=512, maximum=MAX_IMAGE_SIZE, step=64, value=1024)
+                    height = gr.Slider(label="Height", minimum=512, maximum=MAX_IMAGE_SIZE, step=64, value=1024)
+                with gr.Row():
+                    guidance_scale = gr.Slider(label="Guidance Scale", minimum=1, maximum=15, step=0.5, value=7.5)
+                    num_inference_steps = gr.Slider(label="Inference Steps", minimum=1, maximum=30, step=1, value=10)
+
+        with gr.Column(scale=1):
+            gr.Examples(
+                examples=examples,
+                inputs=prompt,
+                cache_examples=False,
+            )
 
     gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
+        triggers=[prompt.submit, run_button.click],
+        fn=generate_images,
         inputs=[
             prompt,
+            style,
             negative_prompt,
             seed,
             randomize_seed,
@@ -224,11 +171,11 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
             height,
             guidance_scale,
             num_inference_steps,
-            style_selection,
-            grid_size_selection,
+            num_images
         ],
-        outputs=[result, seed],
+        outputs=[result_gallery, seed],
+        api_name="generate"
     )
 
 if __name__ == "__main__":
-    demo.launch(ssr_mode=False, show_error=True)
+    demo.queue(max_size=40).launch(ssr_mode=False)