:sparkles: initial commit

.github/workflows/push_to_hub.yml

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+name: Sync to Hugging Face hub
+on:
+  push:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: true
+      - name: Push to hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: git push https://willsh1997:$HF_TOKEN@huggingface.co/spaces/willsh1997/neutral-sd-dev main

README.md

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+---
+title: Neutral Sd Dev
+emoji: 👁
+colorFrom: red
+colorTo: indigo
+sdk: gradio
+sdk_version: 5.12.0
+app_file: gradio_neutral_input_func.py
+pinned: false
+license: apache-2.0
+short_description: neutral sd gradio dev space
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

gradio_neutral_input_func.py

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+import gradio as gr
+import random
+from PIL import Image
+import io
+import json
+import uuid
+import os
+from stable_diffusion_demo import StableDiffusion
+
+# Setup directories
+BASE_DIR = os.path.abspath(os.path.dirname(__file__))
+IMAGE_DIR = os.path.join(BASE_DIR, "neutral_images_storage")
+os.makedirs(IMAGE_DIR, exist_ok=True)
+
+def generate_image():
+    """Generate a neutral image using Stable Diffusion"""
+    generated_image = StableDiffusion(
+        uncond_embeddings=[''],
+        text_embeddings=[''],
+        height=512,
+        width=512,
+        num_inference_steps=25,
+        guidance_scale=7.5,
+        seed=None,
+    )
+    return generated_image
+
+def save_image_and_description(image, description):
+    """Save the generated image and its description"""
+    if image is None:
+        return "No image to save!", None, None
+    
+    if not description:
+        return "Please provide a description!", None, None
+        
+    try:
+        image_id = uuid.uuid4()
+        save_path = os.path.join(IMAGE_DIR, f"{image_id}.png")
+        json_path = os.path.join(IMAGE_DIR, f"{image_id}.json")
+        
+        # Save image
+        image.save(save_path)
+        
+        # Save description
+        desc_json = {"description": description}
+        with open(json_path, "w") as f:
+            json.dump(desc_json, f)
+        
+        # Return success message, clear the image output, and return updated gallery
+        return "Saved successfully!", None, load_previous_examples()
+    except Exception as e:
+        return f"Error saving: {str(e)}", None, None
+
+def load_previous_examples():
+    """Load all previously saved images and descriptions"""
+    examples = []
+    for file in os.listdir(IMAGE_DIR):
+        if file.endswith(".png"):
+            image_id = file.replace(".png", "")
+            image_path = os.path.join(IMAGE_DIR, f"{image_id}.png")
+            json_path = os.path.join(IMAGE_DIR, f"{image_id}.json")
+            
+            if os.path.exists(json_path):
+                image = Image.open(image_path)
+                with open(json_path, "r") as f:
+                    desc = json.load(f)["description"]
+                examples.append((image, desc))
+    return examples
+
+# Create the Gradio interface
+with gr.Blocks(title="Neutral Image App") as demo:
+    gr.Markdown("# Neutral Image App")
+    
+    with gr.Row():
+        with gr.Column():
+            generate_btn = gr.Button("Generate Image")
+            # Disable image upload by setting interactive=False
+            image_output = gr.Image(type="pil", label="Generated Image", interactive=False)
+            description_input = gr.Textbox(label="Describe the image", lines=3)
+            save_btn = gr.Button("Save Image and Description")
+            status_output = gr.Textbox(label="Status")
+    
+    with gr.Accordion("Previous Examples", open=False):
+        gallery = gr.Gallery(
+            label="Previous Images",
+            show_label=True,
+            elem_id="gallery"
+        )#.style(grid=2, height="auto")
+    
+    # Set up event handlers
+    generate_btn.click(
+        fn=generate_image,
+        outputs=[image_output]
+    )
+    
+    # Updated to include gallery refresh in outputs
+    save_btn.click(
+        fn=save_image_and_description,
+        inputs=[image_output, description_input],
+        outputs=[status_output, image_output, gallery]  # Added gallery to outputs
+    )
+    
+    # Load previous examples on startup
+    demo.load(
+        fn=load_previous_examples,
+        outputs=[gallery]
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+pillow
+tqdm
+torch
+transformers
+diffusers
+torchvision
+spaces
+gradio

stable_diffusion_demo.py

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+from PIL import Image
+from tqdm.auto import tqdm
+import torch
+from transformers import CLIPTextModel, CLIPTokenizer
+from diffusers import AutoencoderKL, UNet2DConditionModel, PNDMScheduler, LMSDiscreteScheduler, StableDiffusionPipeline, UniPCMultistepScheduler
+from torchvision import transforms
+import spaces
+
+torch_device = "cuda" if torch.cuda.is_available() else ("mps" if torch.mps.is_available() else "cpu")
+
+torch_dtype = torch.float16 if torch_device in ["cuda", "mps"] else torch.float32
+
+pipe = StableDiffusionPipeline.from_pretrained(
+    "stable-diffusion-v1-5/stable-diffusion-v1-5", 
+    torch_dtype=torch_dtype, 
+    use_safetensors=True, 
+    safety_checker = None).to(torch_device)
+
+pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+
+# pipe.enable_model_cpu_offload() <--- disable for ZeroGPU
+
+@spaces.GPU
+def StableDiffusion(uncond_embeddings, text_embeddings, height, width, num_inference_steps, guidance_scale, seed):
+    batch_size=1
+
+    generator = None
+
+    if seed:
+        generator=torch.manual_seed(seed)
+    
+    output = pipe(
+        prompt = text_embeddings,
+        negative_prompt = uncond_embeddings,
+        height = height,
+        width = width,
+        num_inference_steps = num_inference_steps,
+        guidance_scale = guidance_scale,
+        generator = generator
+    ).images[0]
+    return output
+