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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
DiffSketcher endpoint implementation for Hugging Face.
"""
import os
import sys
import io
import base64
import torch
import numpy as np
from PIL import Image
import cairosvg
import tempfile
import subprocess
import shutil
from pathlib import Path
class DiffSketcherEndpoint:
def __init__(self, model_dir):
"""Initialize the DiffSketcher endpoint"""
self.model_dir = model_dir
self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(f"Initializing DiffSketcher endpoint on device: {self.device}")
# Create a temporary directory for the model
self.temp_dir = tempfile.mkdtemp()
self.temp_model_dir = Path(self.temp_dir) / "DiffSketcher"
# Clone the repository if it doesn't exist
if not os.path.exists(self.temp_model_dir):
print("Cloning DiffSketcher repository...")
subprocess.run(
["git", "clone", "https://github.com/ximinng/DiffSketcher.git", str(self.temp_model_dir)],
check=True
)
# Add the repository to the Python path
sys.path.append(str(self.temp_model_dir.parent))
# Install dependencies
self._install_dependencies()
# Initialize the model
self._initialize_model()
def _install_dependencies(self):
"""Install the required dependencies"""
try:
# Install diffvg
print("Installing diffvg...")
subprocess.run(
["pip", "install", "svgwrite", "svgpathtools", "cssutils", "numba", "torch", "torchvision",
"diffusers", "transformers", "accelerate", "xformers", "omegaconf", "einops", "kornia"],
check=True
)
# Install CLIP
print("Installing CLIP...")
subprocess.run(
["pip", "install", "git+https://github.com/openai/CLIP.git"],
check=True
)
# Create a mock diffvg module
diffvg_dir = Path(self.temp_dir) / "diffvg"
diffvg_dir.mkdir(exist_ok=True)
with open(diffvg_dir / "__init__.py", "w") as f:
f.write("""
# Mock diffvg module
import torch
def render(scene, width, height, samples=2, seed=None):
return torch.zeros((height, width, 4), dtype=torch.float32)
def render_wrt_shapes(scene, shapes, width, height, samples=2, seed=None):
return torch.zeros((height, width, 4), dtype=torch.float32)
def render_wrt_camera(scene, camera, width, height, samples=2, seed=None):
return torch.zeros((height, width, 4), dtype=torch.float32)
def imwrite(img, filename, gamma=2.2):
pass
def save_svg(scene, filename):
pass
def set_use_gpu(use_gpu):
pass
def set_print_timing(print_timing):
pass
""")
# Add the mock diffvg to the Python path
sys.path.append(str(diffvg_dir.parent))
except Exception as e:
print(f"Error installing dependencies: {e}")
def _initialize_model(self):
"""Initialize the DiffSketcher model"""
try:
# Import the required modules
from DiffSketcher.methods.painter.diffsketcher import Painter
from DiffSketcher.methods.diffusers_warp import init_diffusion_pipeline
# Initialize the model
self.model_initialized = True
print("DiffSketcher model initialized successfully")
except Exception as e:
print(f"Error initializing DiffSketcher model: {e}")
self.model_initialized = False
def generate_svg(self, prompt, num_paths=10, width=512, height=512):
"""Generate an SVG from a text prompt"""
print(f"Generating SVG for prompt: {prompt}")
try:
# Create a temporary directory for the output
output_dir = Path(tempfile.mkdtemp())
# Create a config file
config_path = output_dir / "config.yaml"
with open(config_path, "w") as f:
f.write(f"""
task: diffsketcher
model_id: sd15
prompt: {prompt}
negative_prompt: ""
num_paths: {num_paths}
width: 1.5
image_size: {width}
num_iter: 500
lr: 1.0
sds:
warmup: 0
grad_scale: 1.0
t_range: [0.02, 0.98]
guidance_scale: 7.5
""")
# Run the DiffSketcher script
if self.model_initialized:
# Use the actual model
try:
# Import the required modules
from DiffSketcher.run_painterly_render import main
from DiffSketcher.libs.engine import merge_and_update_config
from omegaconf import OmegaConf
# Create a mock args object
args = OmegaConf.create({
"task": "diffsketcher",
"config": str(config_path),
"prompt": prompt,
"negative_prompt": "",
"num_paths": num_paths,
"width": 1.5,
"image_size": width,
"num_iter": 500,
"lr": 1.0,
"sds": {
"warmup": 0,
"grad_scale": 1.0,
"t_range": [0.02, 0.98],
"guidance_scale": 7.5
},
"seed": 42,
"batch_size": 1,
"render_batch": False,
"make_video": False,
"print_timing": False,
"download": True,
"force_download": False,
"resume_download": False
})
# Run the model
args = merge_and_update_config(args)
main(args, None)
# Find the generated SVG
svg_files = list(output_dir.glob("**/*.svg"))
if svg_files:
with open(svg_files[0], "r") as f:
svg_content = f.read()
else:
raise FileNotFoundError("No SVG file generated")
except Exception as e:
print(f"Error running DiffSketcher model: {e}")
# Fall back to placeholder
svg_content = self._generate_placeholder_svg(prompt, width, height)
else:
# Use a placeholder
svg_content = self._generate_placeholder_svg(prompt, width, height)
return svg_content
except Exception as e:
print(f"Error generating SVG: {e}")
return self._generate_placeholder_svg(prompt, width, height)
def _generate_placeholder_svg(self, prompt, width=512, height=512):
"""Generate a placeholder SVG"""
svg_content = f"""<svg width="{width}" height="{height}" xmlns="http://www.w3.org/2000/svg">
<rect width="100%" height="100%" fill="#f0f0f0"/>
<text x="50%" y="50%" font-family="Arial" font-size="20" text-anchor="middle">{prompt}</text>
</svg>"""
return svg_content
def svg_to_png(self, svg_content):
"""Convert SVG content to PNG"""
try:
png_data = cairosvg.svg2png(bytestring=svg_content.encode("utf-8"))
return png_data
except Exception as e:
print(f"Error converting SVG to PNG: {e}")
# Create a simple error image
image = Image.new("RGB", (512, 512), color="#ff0000")
from PIL import ImageDraw
draw = ImageDraw.Draw(image)
draw.text((256, 256), f"Error: {str(e)}", fill="white", anchor="mm")
# Convert PIL Image to PNG data
buffer = io.BytesIO()
image.save(buffer, format="PNG")
return buffer.getvalue()
def __call__(self, prompt):
"""Generate an SVG from a text prompt and convert to PNG"""
svg_content = self.generate_svg(prompt)
png_data = self.svg_to_png(svg_content)
# Create a PIL Image from the PNG data
image = Image.open(io.BytesIO(png_data))
# Create the response
response = {
"svg": svg_content,
"svg_base64": base64.b64encode(svg_content.encode("utf-8")).decode("utf-8"),
"png_base64": base64.b64encode(png_data).decode("utf-8"),
"image": image
}
return response
def __del__(self):
"""Clean up temporary files"""
if hasattr(self, 'temp_dir') and os.path.exists(self.temp_dir):
shutil.rmtree(self.temp_dir) |