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more changes to work with single face operation

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This commit is contained in:
Cowwan 2024-02-06 18:23:07 -05:00
parent 26ae37e79d
commit 797e5c2d56
2 changed files with 12 additions and 20 deletions
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6
facedetection.py
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@ -51,10 +51,10 @@ class FaceDetector():
return []
r = outputs[1, y, x] * 112.
results= [(((x * 4) - r, (y * 4) - r, r*2,r*2))]
results= (((x * 4) - r, (y * 4) - r, r*2,r*2))
results = np.array(results).astype(np.float32)
results[:, [0,2]] *= frame.shape[1] / 224.
results[:, [1,3]] *= frame.shape[0] / 224.
results[ [0,2]] *= frame.shape[1] / 224.
results[ [1,3]] *= frame.shape[0] / 224.
return results
def resizeImage(self, frame):

24
tracker.py
View file

@ -41,8 +41,7 @@ class Tracker():
self.height = height
self.threshold = threshold
self.faces = []
self.face = None
self.face_info = [face.FaceInfo(0, self, featureType)]
self.messageQueue = messageQueue
@ -81,39 +80,32 @@ class Tracker():
def early_exit(self, reason, start):
self.messageQueue.put(reason)
self.faces = []
self.face = None
duration = (time.perf_counter() - start) * 1000
self.messageQueue.put(f"Took {duration:.2f}ms")
return None, None, None
def predict(self, frame, face = None):
def predict(self, frame):
start = time.perf_counter()
duration_fd = 0.0
duration_pp = 0.0
duration_model = 0.0
duration_pnp = 0.0
new_faces = []
new_faces.extend(self.faces)
if face is not None:
new_faces.append(face)
if len(new_faces) < 1:
if self.face is None:
start_fd = time.perf_counter()
new_faces.extend(self.FaceDetector.detect_faces(frame))
self.face = self.FaceDetector.detect_faces(frame)
duration_fd = 1000 * (time.perf_counter() - start_fd)
if len(new_faces) < 1:
if self.face is None:
return self.early_exit("No faces found", start)
crop, crop_info, duration_pp = self.cropFace(new_faces[0], frame)
crop, crop_info, duration_pp = self.cropFace(self.face, frame)
#Early exit if crop fails, If the crop fails there's nothing to track
if crop is None:
return self.early_exit("No valid crops", start)
start_model = time.perf_counter()
#self.Landmarks
conf, lms = self.Landmarks.run(crop , crop_info )
#Early exit if below confidence threshold
if conf < self.threshold:
@ -135,7 +127,7 @@ class Tracker():
lms = face_info.lms[:, 0:2]
x1, y1 = lms[0:66].min(0)
x2, y2 = lms[0:66].max(0)
self.faces = [[y1, x1, y2 - y1, x2 - x1]]
self.face = [y1, x1, y2 - y1, x2 - x1]
duration_pnp += 1000 * (time.perf_counter() - start_pnp)
duration = (time.perf_counter() - start) * 1000
self.messageQueue.put(f"Took {duration:.2f}ms (detect: {duration_fd:.2f}ms, crop: {duration_pp:.2f}ms, track: {duration_model:.2f}ms, 3D points: {duration_pnp:.2f}ms)")