immich-automated-selfie-tim.../main.py
2025-04-06 20:05:14 +02:00

62 lines
2.8 KiB
Python

# main.py
import os
from flask import Flask, request, render_template
from timelapse import process_faces
app = Flask(__name__)
# Read critical parameters from environment variables
DEFAULT_API_KEY = os.environ.get("IMMICH_API_KEY", "")
DEFAULT_BASE_URL = os.environ.get("IMMICH_BASE_URL", "")
DEFAULT_OUTPUT_FOLDER = os.environ.get("IMMICH_OUTPUT_FOLDER", "output")
@app.route("/", methods=["GET", "POST"])
def index():
result = None
error = None
if request.method == "POST":
try:
# Use environment variable defaults if form fields are empty
api_key = request.form.get("api_key") or DEFAULT_API_KEY
base_url = request.form.get("base_url") or DEFAULT_BASE_URL
output_folder = request.form.get("output_folder") or DEFAULT_OUTPUT_FOLDER
person_id = request.form["person_id"]
# Convert numeric parameters with defaults if conversion fails
padding_percent = float(request.form.get("padding_percent", 0.3))
resize_width = int(request.form.get("resize_width", 512))
resize_height = int(request.form.get("resize_height", 512))
min_face_width = int(request.form.get("min_face_width", 128))
min_face_height = int(request.form.get("min_face_height", 128))
pose_threshold = float(request.form.get("pose_threshold", 25))
desired_left_eye_x = float(request.form.get("desired_left_eye_x", 0.35))
desired_left_eye_y = float(request.form.get("desired_left_eye_y", 0.45))
max_workers = int(request.form.get("max_workers", 4))
face_detect_model_path = request.form.get("face_detect_model_path", "mmod_human_face_detector.dat")
landmark_model_path = request.form.get("landmark_model_path", "shape_predictor_68_face_landmarks.dat")
processed_files = process_faces(
api_key=api_key,
base_url=base_url,
person_id=person_id,
output_folder=output_folder,
padding_percent=padding_percent,
resize_width=resize_width,
resize_height=resize_height,
min_face_width=min_face_width,
min_face_height=min_face_height,
pose_threshold=pose_threshold,
desired_left_eye=(desired_left_eye_x, desired_left_eye_y),
max_workers=max_workers,
face_detect_model_path=face_detect_model_path,
landmark_model_path=landmark_model_path
)
result = f"Finished processing. {len(processed_files)} images saved in '{output_folder}'."
except Exception as e:
error = f"Error processing request: {e}"
return render_template("index.html", result=result, error=error)
if __name__ == "__main__":
app.run(host="0.0.0.0", port=5000)