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README.md

@@ -1,10 +1,13 @@
 ---
-title: Playground
-emoji: 🏃
-colorFrom: green
-colorTo: red
-sdk: docker
+title: Playground V2.5
+emoji: 🌍
+colorFrom: pink
+colorTo: green
+sdk: gradio
+sdk_version: 4.8.0
+app_file: app.py
 pinned: false
+license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,158 @@
+#!/usr/bin/env python
+
+import os
+import random
+import uuid
+
+import numpy as np
+from PIL import Image
+import spaces
+import torch
+from diffusers import DiffusionPipeline
+
+
+from flask import Flask, flash, request
+from flask_session import Session
+
+
+app = Flask(__name__)
+app.config["SESSION_PERMANENT"] = False
+app.config["SESSION_TYPE"] = "filesystem"
+
+Session(app)
+
+
+DESCRIPTION = """# Playground v2.5"""
+if not torch.cuda.is_available():
+    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo may not work on CPU.</p>"
+
+MAX_SEED = np.iinfo(np.int32).max
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "1") == "1"
+MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1536"))
+USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
+ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+NUM_IMAGES_PER_PROMPT = 1
+
+if torch.cuda.is_available():
+    pipe = DiffusionPipeline.from_pretrained(
+        "playgroundai/playground-v2.5-1024px-aesthetic",
+        torch_dtype=torch.float16,
+        use_safetensors=True,
+        add_watermarker=False,
+        variant="fp16"
+    )
+    if ENABLE_CPU_OFFLOAD:
+        pipe.enable_model_cpu_offload()
+    else:
+        pipe.to(device)    
+        print("Loaded on Device!")
+    
+    if USE_TORCH_COMPILE:
+        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+        print("Model Compiled!")
+
+
+def save_image(img):
+    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
+
+
+# @spaces.GPU(enable_queue=True)
+def generate(
+    prompt: str,
+    negative_prompt: str = "",
+    use_negative_prompt: bool = False,
+    seed: int = 0,
+    width: int = 1024,
+    height: int = 1024,
+    guidance_scale: float = 3,
+    randomize_seed: bool = False,
+    use_resolution_binning: bool = True,
+):
+    
+    if torch.cuda.is_available():
+        pipe = DiffusionPipeline.from_pretrained(
+            "playgroundai/playground-v2.5-1024px-aesthetic",
+            torch_dtype=torch.float16,
+            use_safetensors=True,
+            add_watermarker=False,
+            variant="fp16"
+        )
+        if ENABLE_CPU_OFFLOAD:
+            pipe.enable_model_cpu_offload()
+        else:
+            pipe.to(device)    
+            print("Loaded on Device!")
+        
+        if USE_TORCH_COMPILE:
+            pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+            print("Model Compiled!")
+
+    pipe.to(device)
+    seed = int(randomize_seed_fn(seed, randomize_seed))
+    generator = torch.Generator().manual_seed(seed)
+
+    if not use_negative_prompt:
+        negative_prompt = None  # type: ignore
+    
+    images = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        width=width,
+        height=height,
+        guidance_scale=guidance_scale,
+        num_inference_steps=25,
+        generator=generator,
+        num_images_per_prompt=NUM_IMAGES_PER_PROMPT,
+        use_resolution_binning=use_resolution_binning,
+        output_type="pil",
+    ).images
+
+    image_paths = [save_image(img) for img in images]
+    print(image_paths)
+    return image_paths, seed
+
+
+examples = [
+    "neon holography crystal cat",
+    "a cat eating a piece of cheese",
+    "an astronaut riding a horse in space",
+    "a cartoon of a boy playing with a tiger",
+    "a cute robot artist painting on an easel, concept art",
+    "a close up of a woman wearing a transparent, prismatic, elaborate nemeses headdress, over the should pose, brown skin-tone"
+]
+
+
+
+@app.route("/", methods=['GET', 'POST'])
+def hello():
+    if request.method == 'POST':
+        if 'file' and 'file1' not in request.files:
+            flash('No file part')
+            return {"status": "Failed", "message": "Please Provide file name(file)."}
+        file = request.files['file']
+        file1 = request.files['file1']
+        image = Image.open(file)
+        image1 = Image.open(file1)
+        preprocess_image = generate('a boy playing with basketball')
+        # print(preprocess_image)
+        return {"status": "Success", "message": "You can download the 3D model.", "data": preprocess_image}
+        
+    else: 
+        return {
+            "status": "Success",
+            "message":"You can upload an image file to get the 3D model."
+        }
+
+if "__main__" == __name__:
+    app.run(debug=True)

requirements.txt

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+accelerate==0.28.0
+aiofiles==23.2.1
+altair==5.2.0
+annotated-types==0.6.0
+anyio==4.3.0
+attrs==23.2.0
+blinker==1.7.0
+cachelib==0.12.0
+certifi==2024.2.2
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+contourpy==1.2.0
+cycler==0.12.1
+diffusers @ git+https://github.com/huggingface/diffusers.git@363699044e365ef977a7646b500402fa585e1b6b
+exceptiongroup==1.2.0
+fastapi==0.110.0
+ffmpy==0.3.2
+filelock==3.13.1
+Flask==3.0.2
+Flask-Session==0.7.0
+fonttools==4.50.0
+fsspec==2024.3.1
+gradio==4.22.0
+gradio_client==0.13.0
+h11==0.14.0
+httpcore==1.0.4
+httpx==0.27.0
+huggingface-hub==0.21.4
+idna==3.6
+importlib_metadata==7.1.0
+importlib_resources==6.4.0
+itsdangerous==2.1.2
+Jinja2==3.1.3
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+kiwisolver==1.4.5
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.8.3
+mdurl==0.1.2
+mpmath==1.3.0
+msgspec==0.18.6
+networkx==3.2.1
+numpy==1.26.4
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu12==2.19.3
+nvidia-nvjitlink-cu12==12.4.99
+nvidia-nvtx-cu12==12.1.105
+orjson==3.9.15
+packaging==24.0
+pandas==2.2.1
+pillow==10.2.0
+psutil==5.9.8
+pydantic==2.6.4
+pydantic_core==2.16.3
+pydub==0.25.1
+Pygments==2.17.2
+pyparsing==3.1.2
+python-dateutil==2.9.0.post0
+python-multipart==0.0.9
+pytz==2024.1
+PyYAML==6.0.1
+referencing==0.34.0
+regex==2023.12.25
+requests==2.31.0
+rich==13.7.1
+rpds-py==0.18.0
+ruff==0.3.4
+safetensors==0.4.2
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.1
+spaces==0.24.2
+starlette==0.36.3
+sympy==1.12
+tokenizers==0.15.2
+tomlkit==0.12.0
+toolz==0.12.1
+torch==2.2.1
+tqdm==4.66.2
+transformers==4.39.1
+triton==2.2.0
+typer==0.10.0
+typing_extensions==4.10.0
+tzdata==2024.1
+urllib3==2.2.1
+uvicorn==0.29.0
+websockets==11.0.3
+Werkzeug==3.0.1
+zipp==3.18.1