def bgsub(vidfile_basename, threshold, quiet=False, drawBoxes=True):
operator = BackgroundSubtractor(2000, threshold, True)
# Learn the bg
operator.model_bg2(VIDEO_DIR + vidfile_basename)
tp_t = fp_t = fn_t = p_t = n_t = 0
video = cv2.VideoCapture(VIDEO_DIR + vidfile_basename)
ret, frame = video.read()
frame_num = 0
while ret:
mask = operator.apply(frame)
mask = tools.morph_openclose(mask)
mask_binary = (mask == 255).astype(np.uint8)
gt_filename = "{0}/{1}/{2}.jpg.seg.bmp".format(GT_IMG_DIR, vidfile_basename, frame_num)
if os.path.exists(gt_filename):
if not quiet:
cv2.imshow("Ground truth", cv2.imread(gt_filename) * 255)
tp, fp, fn = compare_response_to_truth(mask_binary, gt_filename)
# print("True Pos: {0}\nFalse Pos: {1}".format(tp, fp))
pos_detected, neg_detected = class_counter.count_posneg(mask_binary)
tp_t += tp
fp_t += fp
fn_t += fn
p_t += pos_detected
n_t += neg_detected
# print("Foreground pixels: {0}\nBackground pixels: {1}".format(pos_detected, neg_detected))
if not quiet:
mask = ((mask == 255) * 255).astype(np.uint8)
cv2.imshow("Mask", mask)
if drawBoxes:
blob_detect(mask, frame)
else:
cv2.imshow("Frame", frame)
ret, frame = video.read()
frame_num += 1
if handle_keys() is 1: break
with np.errstate(invalid='ignore'):
precision = np.float64(tp_t) / (tp_t + fp_t)
recall = np.float64(tp_t) / (tp_t + fn_t)
if np.isinf(precision) or np.isnan(precision):
precision = 1
if np.isinf(recall) or np.isnan(recall):
recall = 1
return precision, recall
def run(self, as_script=True):
if self.invisible:
cv2.namedWindow("Control")
prev_gray = None
prev_points = []
self.nextTrackID = 0
while True:
# Get frame
ret, frame = self.cam.read()
if not ret:
break
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Segment
fg_mask = self.operator.apply(frame)
fg_mask = ((fg_mask == 255) * 255).astype(np.uint8)
fg_mask = morph_openclose(fg_mask)
# Detect blobs
if "3.0." in cv2.__version__:
_, contours, _ = cv2.findContours((fg_mask.copy()), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_TC89_L1)
else:
contours, _ = cv2.findContours((fg_mask.copy()), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_TC89_L1)
areas, detections = drawing.draw_min_ellipse(contours, frame, MIN_AREA, MAX_AREA, draw=False)
self.areas += areas
# Track
self.predictNewLocations(frame)
assignments, unmatchedTracks, unmatchedDetections = self.assignTracks(detections, frame)
self.updateMatchedTracks(assignments, detections)
self.updateUnmatchedTracks(unmatchedTracks)
self.deleteLostTracks()
self.createNewTracks(detections, unmatchedDetections)
self.showTracks(frame)
# self.showLostTracks(frame)
self.checkTrackCrosses()
# Store frame and go to next
prev_gray = frame_gray
prev_points = detections
self.frame_idx += 1
if not self.invisible:
self.draw_overlays(frame, fg_mask)
cv2.imshow('Tracking', frame)
cv2.imshow("Mask", fg_mask)
delay = FRAME_DELAY
if handle_keys(delay) == 1:
break
# else:
# if handle_keys(delay) == 1:
# break
# Should we continue running or yield some information about the current frame
if as_script: continue
else: pass
# After the video, examine tracks
# self.checkLostTrackCrosses()
self.cam.release()
def run(self, as_script=True):
if self.invisible:
cv2.namedWindow("Control")
prev_gray = None
prev_points = None
while True:
ret, frame = self.cam.read()
if not ret:
break
fg_mask = self.operator.apply(frame)
fg_mask = ((fg_mask == 255) * 255).astype(np.uint8)
fg_mask = morph_openclose(fg_mask)
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if prev_gray is not None and prev_points is not None:
p0 = np.float32([point
for point in prev_points]).reshape(-1, 1, 2)
if drawing.draw_prev_points(frame, prev_points):
# p1, st, err = cv2.calcOpticalFlowPyrLK(prev_gray, frame_gray, p0, None, **lk_params)
frame_gray[fg_mask == 0] = 255
p1, st, err = cv2.calcOpticalFlowPyrLK(
prev_gray, frame_gray, p0, None, **lk_params)
for p_i, p_f in zip(p0.reshape(-1, 2), p1.reshape(-1, 2)):
result = cross(ROI, ROI_W, ROI_H, p_i, p_f)
if result is 1:
self.arrivals += 1
if not self.quiet:
print("Arrival")
elif result is -1:
self.departures += 1
if not self.quiet:
print("Departure")
if self.drawTracks:
drawing.draw_line(frame, tuple(p_i), tuple(p_f))
prev_gray = frame_gray
contours, hier = drawing.draw_contours(frame, fg_mask)
areas, prev_points = drawing.draw_min_ellipse(
contours, frame, MIN_AREA, MAX_AREA)
self.areas += areas
self.frame_idx += 1
if not self.invisible:
self.draw_overlays(frame, fg_mask)
cv2.imshow("Fas", frame_gray)
cv2.imshow('Tracking', frame)
cv2.imshow("Mask", fg_mask)
delay = 33
else:
delay = 1
if handle_keys(delay) == 1:
break
# Should we continue running or yield some information about the current frame
if as_script: continue
else: pass
return self.areas
def run(self, as_script=True):
if self.invisible:
cv2.namedWindow("Control")
prev_gray = None
prev_points = None
while True:
ret, frame = self.cam.read()
if not ret:
break
fg_mask = self.operator.apply(frame)
fg_mask = ((fg_mask == 255) * 255).astype(np.uint8)
fg_mask = morph_openclose(fg_mask)
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if prev_gray is not None and prev_points is not None:
p0 = np.float32([point for point in prev_points]).reshape(-1, 1, 2)
if drawing.draw_prev_points(frame, prev_points):
# p1, st, err = cv2.calcOpticalFlowPyrLK(prev_gray, frame_gray, p0, None, **lk_params)
frame_gray[fg_mask == 0] = 255
p1, st, err = cv2.calcOpticalFlowPyrLK(prev_gray, frame_gray, p0, None, **lk_params)
for p_i, p_f in zip(p0.reshape(-1, 2), p1.reshape(-1, 2)):
result = cross(ROI, ROI_W, ROI_H, p_i, p_f)
if result is 1:
self.arrivals += 1
if not self.quiet:
print("Arrival")
elif result is -1:
self.departures += 1
if not self.quiet:
print("Departure")
if self.drawTracks:
drawing.draw_line(frame, tuple(p_i), tuple(p_f))
prev_gray = frame_gray
contours, hier = drawing.draw_contours(frame, fg_mask)
areas, prev_points = drawing.draw_min_ellipse(contours, frame, MIN_AREA, MAX_AREA)
self.areas += areas
self.frame_idx += 1
if not self.invisible:
self.draw_overlays(frame, fg_mask)
cv2.imshow("Fas", frame_gray)
cv2.imshow('Tracking', frame)
cv2.imshow("Mask", fg_mask)
delay = 33
else:
delay = 1
if handle_keys(delay) == 1:
break
# Should we continue running or yield some information about the current frame
if as_script: continue
else: pass
return self.areas
def run(self, as_script=True):
if self.invisible:
cv2.namedWindow("Control")
prev_gray = None
prev_points = []
self.nextTrackID = 0
while True:
# Get frame
ret, frame = self.cam.read()
if not ret:
break
# Convert frame to grayscale
frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Segment
fg_mask = self.operator.apply(frame)
fg_mask = ((fg_mask == 255) * 255).astype(np.uint8)
fg_mask = morph_openclose(fg_mask)
# Detect blobs
version = int(re.findall(r'\d+', cv2.__version__)[0])
if version == 3:
_, contours, _ = cv2.findContours((fg_mask.copy()), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_TC89_L1)
else:
# Get contours for detected bees using the foreground mask
contours, _ = cv2.findContours((fg_mask.copy()), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_TC89_L1)
areas, detections = drawing.draw_min_ellipse(contours, frame, MIN_AREA, MAX_AREA, draw=False)
self.areas += areas
# Track
self.predictNewLocations(frame)
assignments, unmatchedTracks, unmatchedDetections = self.assignTracks(detections, frame)
self.updateMatchedTracks(assignments, detections)
self.updateUnmatchedTracks(unmatchedTracks)
self.deleteLostTracks()
self.createNewTracks(detections, unmatchedDetections)
self.showTracks(frame)
# self.showLostTracks(frame)
self.checkTrackCrosses()
# Store frame and go to next
prev_gray = frame_gray
prev_points = detections
self.frame_idx += 1
if not self.invisible:
self.draw_overlays(frame, fg_mask)
cv2.imshow('Tracking', frame)
cv2.imshow("Mask", fg_mask)
delay = FRAME_DELAY
if handle_keys(delay) == 1:
break
# else:
# if handle_keys(delay) == 1:
# break
# Should we continue running or yield some information about the current frame
if as_script: continue
else: pass
# After the video, examine tracks
# self.checkLostTrackCrosses()
self.cam.release()