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on
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Running
on
Zero
File size: 1,853 Bytes
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# logging.py
import os
import uuid
import time
from huggingface_hub import CommitScheduler, HfApi
from PIL import Image
APP_VERSION = "0_3"
HF_DATASET_REPO = "LPX55/upscaler_logs" # Change to your dataset repo
HF_TOKEN = os.environ.get("HUGGINGFACE_TOKEN") # Make sure this is set in your environment
LOG_DIR = "logs_" + APP_VERSION
IMAGE_DIR = os.path.join(LOG_DIR, "upscaler")
LOG_FILE = os.path.join(LOG_DIR, f"{int(time.time())}-logs.csv")
os.makedirs(IMAGE_DIR, exist_ok=True)
scheduler = CommitScheduler(
repo_id=HF_DATASET_REPO,
repo_type="dataset",
folder_path=LOG_DIR,
every=5,
private=True,
token=HF_TOKEN,
allow_patterns=["*.csv", "images/*.png", "images/*.webp", "images/*.jpg", "images/*.jpeg"],
path_in_repo="v" + APP_VERSION
)
def log_params(
prompt, scale, steps, controlnet_conditioning_scale, guidance_scale, seed, guidance_end,
before_image, after_image, user=None
):
before_id = str(uuid.uuid4()) + "_before.png"
after_id = str(uuid.uuid4()) + "_after.png"
before_path = os.path.join(IMAGE_DIR, before_id)
after_path = os.path.join(IMAGE_DIR, after_id)
before_image.save(before_path)
after_image.save(after_path)
is_new = not os.path.exists(LOG_FILE)
with open(LOG_FILE, "a", newline='') as f:
import csv
writer = csv.writer(f)
if is_new:
writer.writerow([
"timestamp", "user", "prompt", "scale", "steps", "controlnet_conditioning_scale",
"guidance_scale", "seed", "guidance_end", "before_image", "after_image"
])
writer.writerow([
time.strftime("%Y-%m-%dT%H:%M:%S"),
user or "anonymous",
prompt, scale, steps, controlnet_conditioning_scale,
guidance_scale, seed, guidance_end, before_path, after_path
])
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