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RetinaFace was added as a face detection scheme.

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This commit is contained in:
Emiliana 2020-02-26 00:52:47 +01:00
parent 90c7c9284b
commit cd9cfd9ee8
7 changed files with 208 additions and 9 deletions
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31
tracker.py
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@ -7,6 +7,7 @@ import time
import queue
import threading
import copy
from retinaface import RetinaFaceDetector
def resolve(name):
f = os.path.join(os.path.dirname(__file__), name)
@ -226,7 +227,7 @@ class FaceInfo():
class Tracker():
def __init__(self, width, height, model_type=3, threshold=0.4, max_faces=1, discard_after=5, scan_every=3, bbox_growth=0.0, max_threads=4, silent=False, pnp_quality=1, model_dir=None, no_gaze=False):
def __init__(self, width, height, model_type=3, threshold=0.4, max_faces=1, discard_after=5, scan_every=3, bbox_growth=0.0, max_threads=4, silent=False, pnp_quality=1, model_dir=None, no_gaze=False, use_retinaface=False):
options = onnxruntime.SessionOptions()
options.inter_op_num_threads = 1
options.intra_op_num_threads = max_threads
@ -248,6 +249,10 @@ class Tracker():
else:
model_base_path = model_dir
self.retinaface = RetinaFaceDetector(model_path=os.path.join(model_base_path, "retinaface_opt.onnx"), json_path=os.path.join(model_base_path, "priorbox_384.json"), threads=max_threads, top_k=max_faces)
self.retinaface_slow = RetinaFaceDetector(model_path=os.path.join(model_base_path, "retinaface_opt.onnx"), json_path=os.path.join(model_base_path, "priorbox_384.json"), threads=2, top_k=max_faces)
self.use_retinaface = use_retinaface
# Single face instance with multiple threads
self.session = onnxruntime.InferenceSession(os.path.join(model_base_path, model), sess_options=options)
@ -664,13 +669,23 @@ class Tracker():
new_faces.extend(self.faces)
new_faces.extend(additional_faces)
self.wait_count += 1
if self.detected < self.max_faces:
if self.detected == 0 or self.wait_count >= self.scan_every:
start_fd = time.perf_counter()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
new_faces.extend(list(self.faceCascade.detectMultiScale(gray, 1.3, 4, 0 | cv2.CASCADE_SCALE_IMAGE, (50, 50))))
duration_fd = 1000 * (time.perf_counter() - start_fd)
self.wait_count = 0
if self.detected == 0:
start_fd = time.perf_counter()
new_faces.extend(self.retinaface.detect_retina(frame))
duration_fd = 1000 * (time.perf_counter() - start_fd)
self.wait_count = 0
elif self.detected < self.max_faces:
if self.use_retinaface > 0:
new_faces.extend(self.retinaface_slow.get_results())
if self.wait_count >= self.scan_every:
if self.use_retinaface > 0:
self.retinaface_slow.background_detect(frame)
else:
start_fd = time.perf_counter()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
new_faces.extend(list(self.faceCascade.detectMultiScale(gray, 1.3, 4, 0 | cv2.CASCADE_SCALE_IMAGE, (50, 50))))
duration_fd = 1000 * (time.perf_counter() - start_fd)
self.wait_count = 0
else:
self.wait_count = 0