Update app.py

app.py

@@ -1,3 +1,5 @@
+#!/usr/bin/env python
+
 import os
 import random
 import uuid
@@ -9,13 +11,69 @@ from PIL import Image
 import spaces
 import torch
 from diffusers import DiffusionPipeline
-import face_recognition  # More robust face detection library
 from typing import Tuple
 
-# Check if GPU is available; fallback to CPU if needed
+# Setup rules for bad words (ensure the prompts are kid-friendly)
+bad_words = json.loads(os.getenv('BAD_WORDS', '["violence", "blood", "scary", "death", "ghost"]'))
+default_negative = os.getenv("default_negative","")
+
+def check_text(prompt, negative=""):
+    for i in bad_words:
+        if i in prompt:
+            return True
+    return False
+
+# Kid-friendly styles
+style_list = [
+    {
+        "name": "Cartoon",
+        "prompt": "colorful cartoon {prompt}. vibrant, playful, friendly, suitable for children, highly detailed, bright colors",
+        "negative_prompt": "scary, dark, violent, ugly, realistic",
+    },
+    {
+        "name": "Children's Illustration",
+        "prompt": "children's illustration {prompt}. cute, colorful, fun, simple shapes, smooth lines, highly detailed, joyful",
+        "negative_prompt": "scary, dark, violent, deformed, ugly",
+    },   
+    {
+        "name": "Sticker",
+        "prompt": "children's sticker of {prompt}. bright colors, playful, high resolution, cartoonish",
+        "negative_prompt": "scary, dark, violent, ugly, low resolution",
+    },
+    {
+        "name": "Fantasy",
+        "prompt": "fantasy world for children with {prompt}. magical, vibrant, friendly, beautiful, colorful",
+        "negative_prompt": "dark, scary, violent, ugly, realistic",
+    },
+    {
+        "name": "(No style)",
+        "prompt": "{prompt}",
+        "negative_prompt": "",
+    },
+]
+
+styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
+STYLE_NAMES = list(styles.keys())
+DEFAULT_STYLE_NAME = "Sticker"
+
+def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
+    p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
+    return p.replace("{prompt}", positive), n + negative
+
+DESCRIPTION = """## Children's Sticker Generator
+
+Generate fun and playful stickers for children using AI.
+"""
+
+if not torch.cuda.is_available():
+    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
+
+MAX_SEED = np.iinfo(np.int32).max
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
+
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
-# Initialize the AI model for sticker generation
+# Initialize the DiffusionPipeline
 pipe = DiffusionPipeline.from_pretrained(
     "SG161222/RealVisXL_V3.0_Turbo",  # or any model of your choice
     torch_dtype=torch.float16,
@@ -23,124 +81,193 @@ pipe = DiffusionPipeline.from_pretrained(
     variant="fp16"
 ).to(device)
 
+# Convert mm to pixels for a specific DPI (300) and ensure divisible by 8
+def mm_to_pixels(mm, dpi=300):
+    """Convert mm to pixels and make the dimensions divisible by 8."""
+    pixels = int((mm / 25.4) * dpi)
+    return pixels - (pixels % 8)  # Adjust to the nearest lower multiple of 8
 
-def face_to_sticker(image_path: str) -> Tuple[str, str]:
-    """Detect the face using face_recognition and convert it to a sticker format."""
-    img = face_recognition.load_image_file(image_path)
-    face_locations = face_recognition.face_locations(img)
+# Default sizes for 75mm and 35mm, rounded to nearest multiple of 8
+size_map = {
+    "75mm": (mm_to_pixels(75), mm_to_pixels(75)),  # 75mm in pixels at 300dpi
+    "35mm": (mm_to_pixels(35), mm_to_pixels(35)),  # 35mm in pixels at 300dpi
+}
 
-    if not face_locations:
-        return None, "No face detected. Please upload a clear image with a visible face."
-
-    # Extract the first detected face and return as an image for sticker creation
-    top, right, bottom, left = face_locations[0]
-    face_img = img[top:bottom, left:right]
-    face_img = Image.fromarray(face_img).resize((256, 256))  # Resize face to sticker size
-    
-    face_img_path = f"{uuid.uuid4()}.png"
-    face_img.save(face_img_path)
-    return face_img_path, "Face successfully converted to a sticker."
+# Function to post-process images (transparent or white background)
+def save_image(img, background="transparent"):
+    img = img.convert("RGBA")
+    data = img.getdata()
+    new_data = []
 
+    if background == "transparent":
+        for item in data:
+            # Replace white with transparent
+            if item[0] == 255 and item[1] == 255 and item[2] == 255:
+                new_data.append((255, 255, 255, 0))  # Transparent
+            else:
+                new_data.append(item)
+    elif background == "white":
+        for item in data:
+            new_data.append(item)  # Keep as white
 
-def generate_prompt(clothing: str, pose: str, mood: str) -> str:
-    """Generate a descriptive prompt based on user-selected clothing, pose, and mood."""
-    prompt = f"sticker of a person wearing {clothing} clothes, in a {pose} pose, looking {mood}."
-    return prompt
+    img.putdata(new_data)
+    unique_name = str(uuid.uuid4()) + ".png"
+    img.save(unique_name)
+    return unique_name
 
+def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    return seed
 
-def generate_stickers(prompt: str, face_image: str, guidance_scale: float = 7.5, randomize_seed: bool = False):
-    """Generate stickers using the diffusion model with the given prompt and face."""
+@spaces.GPU(enable_queue=True)
+def generate(
+    prompt: str,
+    negative_prompt: str = "",
+    use_negative_prompt: bool = False,
+    style: str = DEFAULT_STYLE_NAME,
+    seed: int = 0,
+    size: str = "75mm",
+    guidance_scale: float = 3,
+    randomize_seed: bool = False,
+    background: str = "transparent",
+    progress=gr.Progress(track_tqdm=True),
+):
+    if check_text(prompt, negative_prompt):
+        raise ValueError("Prompt contains restricted words.")
     
-    # Adjust seed for variability
-    seed = random.randint(0, MAX_SEED) if randomize_seed else 42
-    generator = torch.Generator(device).manual_seed(seed)
+    # Ensure prompt is 2-3 words long
+    prompt = " ".join(re.findall(r'\w+', prompt)[:3])
+
+    # Apply style
+    prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
+    seed = int(randomize_seed_fn(seed, randomize_seed))
+    generator = torch.Generator().manual_seed(seed)
+
+    # Ensure we have only white or transparent background options
+    width, height = size_map.get(size, (1024, 1024))
+
+    if not use_negative_prompt:
+        negative_prompt = ""  # type: ignore
 
-    # Prepare AI model options
     options = {
         "prompt": prompt,
-        "width": 512,
-        "height": 512,
+        "negative_prompt": negative_prompt,
+        "width": width,
+        "height": height,
         "guidance_scale": guidance_scale,
-        "num_inference_steps": 50,
+        "num_inference_steps": 25,
         "generator": generator,
+        "num_images_per_prompt": 6,  # Max 6 images
+        "output_type": "pil",
     }
-
-    # Load the face as an input condition for the sticker (optional, if supported by the model)
-    # If your model supports conditioning on a specific face, load the face image here
-    # options['image'] = Image.open(face_image)
-
+    
+    # Generate images with the pipeline
     images = pipe(**options).images
-    image_paths = [save_image(img) for img in images]
+    image_paths = [save_image(img, background) for img in images]
     
     return image_paths, seed
 
+examples = [
+    "cute bunny",
+    "happy cat",
+    "funny dog",
+]
 
-def save_image(img: Image.Image) -> str:
-    """Save an image to a file and return the path."""
-    unique_name = f"{uuid.uuid4()}.png"
-    img.save(unique_name)
-    return unique_name
-
-
-def stick_me_workflow(image, clothing, pose, mood, randomize_seed: bool):
-    """Workflow to generate stickers based on user-uploaded image and options."""
-    # Convert the uploaded image to a face sticker
-    face_path, message = face_to_sticker(image)
-    
-    if face_path is None:
-        return message  # Return error message if face detection fails
-
-    # Generate a descriptive prompt based on user selections
-    prompt = generate_prompt(clothing, pose, mood)
-    
-    # Generate stickers using the diffusion model with the extracted face and prompt
-    stickers, seed = generate_stickers(prompt, face_path, randomize_seed=randomize_seed)
-    return stickers
-
-
-def on_fallback_to_cpu():
-    """Notify users when the app is running on CPU (due to GPU quota being exceeded)."""
-    if not torch.cuda.is_available():
-        return "Warning: GPU quota exceeded. Running on CPU, which will be significantly slower."
-    return ""
+css = '''
+.gradio-container{max-width: 700px !important}
+h1{text-align:center}
+'''
 
-
-# Gradio interface setup
-
-with gr.Blocks() as demo:
-    gr.Markdown("# Sticker Generator with 'Stick Me' Feature")
-
-    # GPU Quota Handling
-    gpu_warning = gr.Markdown(on_fallback_to_cpu(), visible=not torch.cuda.is_available())
-
-    # New Stick Me Option
-    with gr.Row():
-        face_input = gr.Image(label="Upload Your Image for 'Stick Me'", type="filepath")
-        clothing = gr.Dropdown(["Casual", "Formal", "Sports"], label="Choose Clothing")
-        pose = gr.Dropdown(["Standing", "Sitting", "Running"], label="Choose Pose")
-        mood = gr.Dropdown(["Happy", "Serious", "Excited"], label="Choose Mood")
-        randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
-    
-        stick_me_button = gr.Button("Generate Stick Me Stickers")
-    
-    stick_me_result = gr.Gallery(label="Your Stick Me Stickers")
-    
-    stick_me_button.click(
-        fn=stick_me_workflow,
-        inputs=[face_input, clothing, pose, mood, randomize_seed],
-        outputs=[stick_me_result]
+# Define the Gradio UI for the sticker generator
+with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(
+        value="Duplicate Space for private use",
+        elem_id="duplicate-button",
+        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
     )
-    
-    gr.Markdown("# Generate Regular Stickers")
+    with gr.Group():
+        with gr.Row():
+            prompt = gr.Text(
+                label="Enter your prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter 2-3 word prompt (e.g., cute bunny)",
+                container=False,
+            )
+            run_button = gr.Button("Run")
+        result = gr.Gallery(label="Generated Stickers", columns=2, preview=True)
+    with gr.Accordion("Advanced options", open=False):
+        use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
+        negative_prompt = gr.Text(
+            label="Negative prompt",
+            max_lines=1,
+            placeholder="Enter a negative prompt",
+            value="(scary, violent, dark, ugly)",
+            visible=True,
+        )
+        seed = gr.Slider(
+            label="Seed",
+            minimum=0,
+            maximum=MAX_SEED,
+            step=1,
+            value=0,
+            visible=True
+        )
+        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+        size_selection = gr.Radio(
+            choices=["75mm", "35mm"],
+            value="75mm",
+            label="Sticker Size",
+        )
+        style_selection = gr.Radio(
+            choices=STYLE_NAMES,
+            value=DEFAULT_STYLE_NAME,
+            label="Image Style",
+        )
+        background_selection = gr.Radio(
+            choices=["transparent", "white"],
+            value="transparent",
+            label="Background Color",
+        )
+        guidance_scale = gr.Slider(
+            label="Guidance Scale",
+            minimum=0.1,
+            maximum=20.0,
+            step=0.1,
+            value=6,
+        )
 
-    prompt = gr.Textbox(label="Enter a Prompt for Sticker Creation", placeholder="Cute bunny", max_lines=1)
-    generate_button = gr.Button("Generate Stickers")
-    result = gr.Gallery(label="Generated Stickers")
+    gr.Examples(
+        examples=examples,
+        inputs=prompt,
+        outputs=[result, seed],
+        fn=generate,
+        cache_examples=CACHE_EXAMPLES,
+    )
 
-    generate_button.click(
-        fn=generate_stickers,
-        inputs=[prompt],
-        outputs=[result]
+    gr.on(
+        triggers=[
+            prompt.submit,
+            negative_prompt.submit,
+            run_button.click,
+        ],
+        fn=generate,
+        inputs=[
+            prompt,
+            negative_prompt,
+            use_negative_prompt,
+            style_selection,
+            seed,
+            size_selection,
+            guidance_scale,
+            randomize_seed,
+            background_selection,
+        ],
+        outputs=[result, seed],
+        api_name="run",
     )
 
-    demo.launch()
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()