diff --git a/main.py b/main.py
index a4bb334..499bf80 100644
--- a/main.py
+++ b/main.py
@@ -1,6 +1,7 @@
import os
import multiprocessing
-from flask import Flask, request, render_template
+import threading
+from flask import Flask, request, render_template, jsonify
from timelapse import process_faces
app = Flask(__name__)
@@ -17,43 +18,67 @@ LANDMARK_MODEL = "shape_predictor_68_face_landmarks.dat"
LEFT_EYE_POS = (0.35, 0.45)
AVAILABLE_CORES = multiprocessing.cpu_count()
+# Global progress dictionary – only one job at a time is assumed here
+progress_info = {"completed": 0, "total": 0, "status": "idle"}
+
+def update_progress(current, total):
+ progress_info["completed"] = current
+ progress_info["total"] = total
+ progress_info["status"] = "running" if current < total else "done"
+
+def background_process(person_id, padding_percent, resize_size, face_resolution_threshold, pose_threshold, max_workers):
+ try:
+ progress_info["status"] = "running"
+ 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_size,
+ resize_height=resize_size,
+ min_face_width=face_resolution_threshold,
+ min_face_height=face_resolution_threshold,
+ pose_threshold=pose_threshold,
+ desired_left_eye=LEFT_EYE_POS,
+ max_workers=max_workers,
+ face_detect_model_path=FACE_DETECT_MODEL,
+ landmark_model_path=LANDMARK_MODEL,
+ progress_callback=update_progress
+ )
+ except Exception as e:
+ progress_info["status"] = f"error: {e}"
+ else:
+ progress_info["status"] = "done"
+
+@app.route("/progress")
+def progress():
+ return jsonify(progress_info)
+
@app.route("/", methods=["GET", "POST"])
def index():
result = None
error = None
- # Create max_workers_options as a list of numbers from 1 to AVAILABLE_CORES
+ # Create max_workers_options as a list from 1 to AVAILABLE_CORES
max_workers_options = list(range(1, AVAILABLE_CORES + 1))
if request.method == "POST":
try:
- api_key = API_KEY
- base_url = BASE_URL
- output_folder = OUTPUT_FOLDER
-
- # Get user input from the form
person_id = request.form["person_id"]
padding_percent = float(request.form.get("padding_percent", 30)) / 100
resize_size = int(request.form.get("resize_size", 512))
face_resolution_threshold = int(request.form.get("face_resolution_threshold", 128))
pose_threshold = float(request.form.get("pose_threshold", 25))
max_workers = int(request.form.get("max_workers", 1)) # default is 1
-
- 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_size,
- resize_height=resize_size,
- min_face_width=face_resolution_threshold,
- min_face_height=face_resolution_threshold,
- pose_threshold=pose_threshold,
- desired_left_eye=LEFT_EYE_POS,
- max_workers=max_workers,
- face_detect_model_path=FACE_DETECT_MODEL,
- landmark_model_path=LANDMARK_MODEL
- )
- result = f"Finished processing. {len(processed_files)} images saved in '{output_folder}'."
+ # Reset progress info before starting
+ progress_info["completed"] = 0
+ progress_info["total"] = 0
+ progress_info["status"] = "idle"
+ # Start the processing in a background thread
+ threading.Thread(
+ target=background_process,
+ args=(person_id, padding_percent, resize_size, face_resolution_threshold, pose_threshold, max_workers)
+ ).start()
+ result = "Processing started. Please wait and watch the progress bar below."
except Exception as e:
error = f"Error processing request: {e}"
return render_template("index.html", result=result, error=error, max_workers_options=max_workers_options)
diff --git a/templates/index.html b/templates/index.html
index 5b2710d..9e9d241 100644
--- a/templates/index.html
+++ b/templates/index.html
@@ -65,6 +65,14 @@
.result {
color: #080;
}
+ #progressContainer {
+ margin-top: 20px;
+ text-align: center;
+ }
+ progress {
+ width: 100%;
+ height: 25px;
+ }
@@ -107,6 +115,30 @@
{% if result %}
{{ result }}
{% endif %}
+
+
+