copilot/OpenSeeFace
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

This changes the points used for PnP solving and replaces the RetinaFace model with a higher resolution version.

Browse source
This commit is contained in:
Emiliana 2020-02-28 02:10:23 +01:00
parent 4a88c57be2
commit 033a48b132
8 changed files with 49 additions and 45 deletions
Download patch file Download diff file Expand all files Collapse all files

22
retinaface.py
View file

@ -59,7 +59,7 @@ def worker_thread(rfd, frame):
rfd.running = False
class RetinaFaceDetector():
def __init__(self, model_path="models/retinaface_opt.onnx", json_path="models/priorbox_384.json", threads=4, min_conf=0.3, nms_threshold=0.4, top_k=1):
def __init__(self, model_path="models/retinaface_640x640_opt.onnx", json_path="models/priorbox_640x640.json", threads=4, min_conf=0.4, nms_threshold=0.4, top_k=1, res=(640, 640)):
options = onnxruntime.SessionOptions()
options.inter_op_num_threads = 1
options.intra_op_num_threads = threads
@ -67,7 +67,7 @@ class RetinaFaceDetector():
options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
options.log_severity_level = 3
self.session = onnxruntime.InferenceSession(model_path, sess_options=options)
self.res = 384
self.res_w, self.res_h = res
with open(json_path, "r") as prior_file:
self.priorbox = np.array(json.loads(prior_file.read()))
self.min_conf = min_conf
@ -81,18 +81,18 @@ class RetinaFaceDetector():
h, w, _ = frame.shape
im = None
if h > w:
resize = h / self.res
im = cv2.resize(frame, (int(w / resize), self.res), interpolation=cv2.INTER_LINEAR)
resize = h / self.res_h
im = cv2.resize(frame, (int(w / resize), self.res_h), interpolation=cv2.INTER_LINEAR)
resize = 1 / resize
else:
resize = w / self.res
im = cv2.resize(frame, (self.res, int(h / resize)), interpolation=cv2.INTER_LINEAR)
resize = w / self.res_w
im = cv2.resize(frame, (self.res_w, int(h / resize)), interpolation=cv2.INTER_LINEAR)
resize = 1 / resize
pad_h = self.res - im.shape[0]
pad_w = self.res - im.shape[1]
pad_h = self.res_h - im.shape[0]
pad_w = self.res_w - im.shape[1]
im = cv2.copyMakeBorder(im, 0, pad_h, 0, pad_w, cv2.BORDER_CONSTANT, (0, 0, 0))
im = np.float32(im)
scale = np.array((self.res, self.res, self.res, self.res))
scale = np.array((self.res_w, self.res_h, self.res_w, self.res_h))
im -= (104, 117, 123)
im = im.transpose(2, 0, 1)
im = np.expand_dims(im, 0)
@ -112,8 +112,8 @@ class RetinaFaceDetector():
dets = dets[:self.top_k, 0:4]
dets[:, 2:4] = dets[:, 2:4] - dets[:, 0:2]
if is_background:
upsize = dets[:, 2:4] * np.array([[0.1, 0.0]])
if True:#is_background:
upsize = dets[:, 2:4] * np.array([[0.15, 0.2]])
dets[:, 0:2] -= upsize
dets[:, 2:4] += upsize * 2