From 57f0e4f8f7ccd53d900381421ac426ec74dbf37a Mon Sep 17 00:00:00 2001
From: "google-labs-jules[bot]"
<161369871+google-labs-jules[bot]@users.noreply.github.com>
Date: Sat, 21 Mar 2026 06:23:11 +0000
Subject: [PATCH 1/3] feat: enhance face detection with GPU support, privacy
mode, and gallery
- Added GPU support (CUDA) to the YOLOv12 detector if available.
- Implemented `blur_faces` method in `YOLOv12FaceDetector` for privacy-conscious detections.
- Implemented `get_face_crops` method to extract and gallery detected faces.
- Updated `/api/detect-image` to support an optional `blur` parameter and return base64 face crops.
- Added a Dark Mode toggle to the web UI with persistent theme settings.
- Added a "Privacy Mode (Blur Faces)" toggle and a "Face Gallery" section to the UI.
- Cleaned up the repository of temporary test and mock files.
Co-authored-by: RevDra <200167038+RevDra@users.noreply.github.com>
---
src/face_detection_yolov12.py | 58 +++++++++++++++++++++-
src/web_app.py | 20 ++++++--
web/templates/index.html | 91 ++++++++++++++++++++++++++++++++---
3 files changed, 157 insertions(+), 12 deletions(-)
diff --git a/src/face_detection_yolov12.py b/src/face_detection_yolov12.py
index f2c9ba2..59e4e41 100644
--- a/src/face_detection_yolov12.py
+++ b/src/face_detection_yolov12.py
@@ -30,8 +30,9 @@ def __init__(self, model_path):
try:
from ultralytics import YOLO
- self.yolo = YOLO(model_path)
- print(f"Loaded YOLOv12 model from {model_path}")
+ self.device = "cuda" if torch.cuda.is_available() else "cpu"
+ self.yolo = YOLO(model_path).to(self.device)
+ print(f"Loaded YOLOv12 model from {model_path} on {self.device}")
except ImportError:
raise ImportError("ultralytics package not found. pip install ultralytics")
except Exception as e:
@@ -136,6 +137,59 @@ def draw_faces(self, image, detections, color=(0, 255, 0), thickness=2, show_con
)
return result
+ def blur_faces(self, image, detections, blur_factor=30):
+ """Apply Gaussian blur to detected faces for privacy"""
+ result = image.copy()
+ h, w = image.shape[:2]
+
+ for det in detections:
+ x1, y1, x2, y2 = det["x1"], det["y1"], det["x2"], det["y2"]
+
+ # Ensure coordinates are within image boundaries
+ x1, y1 = max(0, x1), max(0, y1)
+ x2, y2 = min(w, x2), min(h, y2)
+
+ if x2 > x1 and y2 > y1:
+ # Extract the face ROI from the ORIGINAL image to avoid cumulative blur
+ # but here we work on result which is a copy.
+ face_roi = image[y1:y2, x1:x2]
+
+ # Ensure kernel size is odd and based on face size
+ kw = (x2 - x1) // 2
+ kh = (y2 - y1) // 2
+
+ # Minimum kernel size for noticeable blur
+ kw = max(25, kw if kw % 2 != 0 else kw + 1)
+ kh = max(25, kh if kh % 2 != 0 else kh + 1)
+
+ # Use BORDER_DEFAULT (reflection) for better visual result
+ blurred_face = cv2.GaussianBlur(face_roi, (kw, kh), blur_factor)
+ result[y1:y2, x1:x2] = blurred_face
+
+ return result
+
+ def get_face_crops(self, image, detections, padding=0.1):
+ """Extract cropped face images from detection results"""
+ crops = []
+ h, w = image.shape[:2]
+
+ for det in detections:
+ x1, y1, x2, y2 = det["x1"], det["y1"], det["x2"], det["y2"]
+ fw, fh = x2 - x1, y2 - y1
+
+ # Add padding
+ px = int(fw * padding)
+ py = int(fh * padding)
+
+ cx1, cy1 = max(0, x1 - px), max(0, y1 - py)
+ cx2, cy2 = min(w, x2 + px), min(h, y2 + py)
+
+ if cx2 > cx1 and cy2 > cy1:
+ crop = image[cy1:cy2, cx1:cx2]
+ crops.append(crop)
+
+ return crops
+
# --- GUI Class (Webcam) ---
class WebcamFaceDetectionGUI:
diff --git a/src/web_app.py b/src/web_app.py
index f9fa948..45d6ab2 100644
--- a/src/web_app.py
+++ b/src/web_app.py
@@ -148,8 +148,10 @@ def detect_image():
if not allowed_file(file.filename) or not is_image(file.filename):
return jsonify({"error": "Only image files allowed"}), 400
- # Get model selection
+ # Get parameters
model = request.form.get("model", "yolov12l-face.pt")
+ blur = request.form.get("blur") == "true"
+
if model not in ALLOWED_MODELS:
app.logger.info(f"Invalid model '{model}' requested. Fallback to default.")
model = "yolov12l-face.pt"
@@ -171,12 +173,23 @@ def detect_image():
# Use standard detection for uploaded files
detections = detector.detect_faces(image, conf_threshold=0.32)
- # Draw detections
- result_image = detector.draw_faces(image, detections, show_confidence=True)
+ # Process image: Draw or Blur
+ if blur:
+ result_image = detector.blur_faces(image, detections)
+ else:
+ result_image = detector.draw_faces(image, detections, show_confidence=True)
if result_image is None:
return jsonify({"error": "Failed to process image"}), 500
+ # Extract crops for gallery
+ crops_base64 = []
+ if len(detections) > 0:
+ crops = detector.get_face_crops(image, detections)
+ for crop in crops:
+ _, buffer = cv2.imencode(".jpg", crop)
+ crops_base64.append(base64.b64encode(buffer).decode())
+
# Convert result to base64 for display
_, buffer = cv2.imencode(".jpg", result_image)
img_base64 = base64.b64encode(buffer).decode()
@@ -197,6 +210,7 @@ def detect_image():
}
for i, det in enumerate(detections)
],
+ "crops": crops_base64
},
}
diff --git a/web/templates/index.html b/web/templates/index.html
index 84ca4cd..ec38c7a 100644
--- a/web/templates/index.html
+++ b/web/templates/index.html
@@ -6,9 +6,18 @@
YOLOv12 Face Detection - Web