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added logging to file

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henrisel 2025-11-14 09:53:30 +02:00
parent 590c62eadd
commit d7fec73c77
2 changed files with 25 additions and 2 deletions
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3
3d-generation-pipeline/.gitignore vendored
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@ -2,4 +2,5 @@
.env .env
__pycache__ __pycache__
images/ images/
models/ models/
logs/

24
3d-generation-pipeline/start_pipeline.py
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@ -1,6 +1,8 @@
import os import os
import argparse import argparse
import asyncio import asyncio
import logging
import time
from pathlib import Path from pathlib import Path
from datetime import datetime from datetime import datetime
@ -18,6 +20,16 @@ PIPELINE_FOLDER = os.environ["PIPELINE_FOLDER"]
def get_timestamp(): def get_timestamp():
return datetime.now().strftime("%Y-%m-%d-%H-%M-%S") return datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
def setup_logger(base_folder, timestamp):
log_dir = base_folder / Path("logs")
log_dir.mkdir(parents=True, exist_ok=True)
logging.basicConfig(
filename=log_dir / f"{timestamp}.log",
level=logging.INFO,
#format='%(asctime)s - %(message)s'
force=True
)
async def main(): async def main():
parser = argparse.ArgumentParser(description="Text to 3D model pipeline") parser = argparse.ArgumentParser(description="Text to 3D model pipeline")
@ -34,16 +46,26 @@ async def main():
else: else:
image_generation_prompt = input_prompt image_generation_prompt = input_prompt
timestamp = get_timestamp()
pipeline_folder = Path(PIPELINE_FOLDER) pipeline_folder = Path(PIPELINE_FOLDER)
timestamp = get_timestamp()
setup_logger(pipeline_folder, timestamp)
time_checkpoint = time.time()
image_path = pipeline_folder / "images" / f"{timestamp}.jpg" image_path = pipeline_folder / "images" / f"{timestamp}.jpg"
# TODO: use Invoke AI or Cloudflare, depending on env var # TODO: use Invoke AI or Cloudflare, depending on env var
#text_to_image_cloudflare(image_generation_prompt, image_path) #text_to_image_cloudflare(image_generation_prompt, image_path)
await text_to_image_invoke_ai(image_generation_prompt, image_path) await text_to_image_invoke_ai(image_generation_prompt, image_path)
image_generation_time = time.time() - time_checkpoint
time_checkpoint = time.time()
logging.info(f"Image generation time: {round(image_generation_time, 1)} s")
print(f"Generated image file: {image_path}") print(f"Generated image file: {image_path}")
model_path = pipeline_folder / "models" / timestamp model_path = pipeline_folder / "models" / timestamp
model_file = image_to_3d_api(image_path, model_path) model_file = image_to_3d_api(image_path, model_path)
model_generation_time = time.time() - time_checkpoint
logging.info(f"Model generation time: {round(model_generation_time, 1)} s")
print(f"Generated 3D model file: {model_file}") print(f"Generated 3D model file: {model_file}")