97 lines
2.8 KiB
Python
97 lines
2.8 KiB
Python
import subprocess
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import os
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import time
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import requests
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import base64
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from dotenv import load_dotenv
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load_dotenv()
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MODEL_FOLDER = os.environ["MODEL_FOLDER"]
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API_URL = os.environ["3D_GENERATION_URL"]
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def image_to_3d_subprocess(image_path, output_path):
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venv_python = MODEL_FOLDER + r"\.venv\Scripts\python.exe"
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script_path = MODEL_FOLDER + r"\run.py"
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args = [image_path, "--output-dir", output_path]
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command = [venv_python, script_path] + args
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try:
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# Run the subprocess
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result = subprocess.run(command, capture_output=True, text=True)
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# Print output and errors
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print("STDOUT:\n", result.stdout)
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print("STDERR:\n", result.stderr)
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print("Return Code:", result.returncode)
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except Exception as e:
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print(f"Error occurred: {e}")
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def generate_no_preview(image_base64: str):
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"""Generate 3D model from a single base64-encoded image without previews.
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Args:
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image_base64: Base64 string of the image (without 'data:image/...' prefix)
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"""
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try:
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# Set generation parameters
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params = {
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'image_base64': image_base64,
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'seed': 42,
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'ss_guidance_strength': 7.5,
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'ss_sampling_steps': 10,
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'slat_guidance_strength': 7.5,
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'slat_sampling_steps': 10,
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'mesh_simplify_ratio': 0.97,
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'texture_size': 1024,
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#'texture_baking_mode': 'opt',
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'texture_opt_total_steps': 1000,
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'output_format': 'glb'
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}
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# Start generation
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print("Starting generation...")
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response = requests.post(f"{API_URL}/generate_no_preview", data=params)
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response.raise_for_status()
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# Poll status until complete
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while True:
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status = requests.get(f"{API_URL}/status").json()
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print(f"Progress: {status['progress']}%")
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if status['status'] == 'COMPLETE':
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break
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elif status['status'] == 'FAILED':
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raise Exception(f"Generation failed: {status['message']}")
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time.sleep(1)
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# Download the model
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print("Downloading model...")
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response = requests.get(f"{API_URL}/download/model")
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response.raise_for_status()
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return response.content
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except Exception as e:
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print(f"Error: {str(e)}")
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return None
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def image_to_3d_api(image_path, output_path):
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with open(image_path, 'rb') as image_file:
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image_data = image_file.read()
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base64_encoded = base64.b64encode(image_data).decode('utf-8')
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model_binary = generate_no_preview(base64_encoded)
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output_file = f"{output_path}.glb"
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with open(output_file, 'wb') as f:
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f.write(model_binary)
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return output_file
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