Update app.py

app.py

@@ -1,198 +1,64 @@
 import gradio as gr
-import numpy as np
-import random
+import threading
 import os
-
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
 import torch
 
-from fastapi import FastAPI
-
-app = FastAPI()
-
-#----------Start of theme----------
-theme = gr.themes.Soft(
-    primary_hue="zinc",
-    secondary_hue="stone",
-    font=[gr.themes.GoogleFont('Kavivanar'), gr.themes.GoogleFont('Kavivanar'), 'system-ui', 'sans-serif'],
-    font_mono=[gr.themes.GoogleFont('Source Code Pro'), gr.themes.GoogleFont('Inconsolata'), gr.themes.GoogleFont('Inconsolata'), 'monospace'],
-).set(
-    body_background_fill='*primary_100',
-    body_text_color='secondary_600',
-    body_text_color_subdued='*primary_500',
-    body_text_weight='500',
-    background_fill_primary='*primary_100',
-    background_fill_secondary='*secondary_200',
-    color_accent='*primary_300',
-    border_color_accent_subdued='*primary_400',
-    border_color_primary='*primary_400',
-    block_background_fill='*primary_300',
-    block_border_width='*panel_border_width',
-    block_info_text_color='*primary_700',
-    block_info_text_size='*text_md',
-    panel_background_fill='*primary_200',
-    accordion_text_color='*primary_600',
-    slider_color='*primary_500',
-    table_text_color='*primary_600',
-    input_background_fill='*primary_50',
-    input_background_fill_focus='*primary_100',
-    button_primary_background_fill='*primary_500',
-    button_primary_background_fill_hover='*primary_400',
-    button_primary_text_color='*primary_50',
-    button_primary_text_color_hover='*primary_100',
-    button_cancel_background_fill='*primary_500',
-    button_cancel_background_fill_hover='*primary_400'
-)
-#----------End of theme----------
-
-API_TOKEN = os.getenv("HF_READ_TOKEN")
-headers = {"Authorization": f"Bearer {API_TOKEN}"}
-timeout = 100
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
-
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
-
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
-
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
-def infer(
-    prompt,
-    negative_prompt,
-    seed,
-    randomize_seed,
-    width,
-    height,
-    guidance_scale,
-    num_inference_steps,
-    progress=gr.Progress(track_tqdm=True),
-):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-
-    generator = torch.Generator().manual_seed(seed)
+os.environ["OMP_NUM_THREADS"] = str(os.cpu_count())
+torch.set_num_threads(os.cpu_count())
 
-    image = pipe(
-        prompt=prompt,
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale,
-        num_inference_steps=num_inference_steps,
-        width=width,
-        height=height,
-        generator=generator,
-    ).images[0]
+model1 = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA")
+model2 = gr.load("models/Purz/face-projection")
 
-    return image, seed
+stop_event = threading.Event()
 
+def generate_images(text, selected_model):
+    stop_event.clear()
 
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
+    if selected_model == "Model 1 (Turbo Realism)":
+        model = model1
+    elif selected_model == "Model 2 (Face Projection)":
+        model = model2
+    else:
+        return ["Invalid model selection."] * 3
 
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-}
-"""
+    results = []
+    for i in range(3):
+        if stop_event.is_set():
+            return ["Image generation stopped by user."] * 3
 
-with gr.Blocks(theme=theme, css=css) as app:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image")
+        modified_text = f"{text} variation {i+1}"
+        result = model(modified_text)
+        results.append(result)
 
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=5,
-                placeholder="Enter your prompt",
-                container=False,
-            )
+    return results
 
-            run_button = gr.Button("Run", scale=0, variant="primary")
+def stop_generation():
+    """Stops the ongoing image generation by setting the stop_event flag."""
+    stop_event.set()
+    return ["Generation stopped."] * 3
 
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=5,
-                placeholder="(visible hand:1.3), (ugly:1.3), (duplicate:1.2), (morbid:1.1), (mutilated:1.1), out of frame, bad face, extra fingers, mutated hands, (poorly drawn hands:1.1), (poorly drawn face:1.3), (mutation:1.3), (deformed:1.3), blurry, (bad anatomy:1.1), (bad proportions:1.2), (extra limbs:1.1), cloned face, (disfigured:1.2), gross proportions, malformed limbs, (missing arms:1.1), (missing legs:1.1), (extra arms:1.2), (extra legs:1.2), fused fingers, too many fingers, (long neck:1.2), sketched by bad-artist, (bad-image-v2-39000:1.3)",
-                visible=False,
-            )
-
-            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=32,
-                    value=896,  # Replace with defaults that work for your model
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=512,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1150,  # Replace with defaults that work for your model
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=5.0,  # Replace with defaults that work for your model
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=30,  # Replace with defaults that work for your model
-                )
-
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
+with gr.Blocks() as interface:#...
+    gr.Markdown(
+        "### ⚠ Sorry for the inconvenience. The Space is currently running on the CPU, which might affect performance. We appreciate your understanding."
     )
-
-if __name__ == "__main__":
-    app.launch()
+    
+    text_input = gr.Textbox(label="Type here your imagination:", placeholder="Type your prompt...")
+    model_selector = gr.Radio(
+        ["Model 1 (Turbo Realism)", "Model 2 (Face Projection)"],
+        label="Select Model",
+        value="Model 1 (Turbo Realism)"
+    )
+    
+    with gr.Row():
+        generate_button = gr.Button("Generate 3 Images 🎨")
+        stop_button = gr.Button("Stop Image Generation")
+    
+    with gr.Row():
+        output1 = gr.Image(label="Generated Image 1")
+        output2 = gr.Image(label="Generated Image 2")
+        output3 = gr.Image(label="Generated Image 3")
+    
+    generate_button.click(generate_images, inputs=[text_input, model_selector], outputs=[output1, output2, output3])
+    stop_button.click(stop_generation, inputs=[], outputs=[output1, output2, output3])
+
+interface.launch()