def get_heartrate(filename, dir):
""" Read video file and estimate heart rate """
# Frequency range for Fast-Fourier Transform
freq_min = 1
freq_max = 1.8
# Preprocessing phase
hr = -1 # Valor por defecto
fn = os.path.join(dir, filename)
video_frames, frame_ct, fps = preprocessing.read_video(fn)
# Build Laplacian video pyramid
lap_video = pyramids.build_video_pyramid(video_frames)
amplified_video_pyramid = []
for i, video in enumerate(lap_video):
if i == 0 or i == len(lap_video) - 1:
continue
# Eulerian magnification with temporal FFT filtering
result, fft, frequencies = eulerian.fft_filter(video, freq_min,
freq_max, fps)
lap_video[i] += result
# Calculate heart rate
hr = find_heart_rate(fft, frequencies, freq_min, freq_max)
filename, _ = os.path.splitext(filename)
return hr, filename
def mMain(pPath):
# Frequency range for Fast-Fourier Transform
freq_min = 1
freq_max = 1.8
# Preprocessing phase
# print("Reading + preprocessing video...")
video_frames, frame_ct, fps = preprocessing.read_video("videos/" + pPath)
# Build Laplacian video pyramid
# print("Building Laplacian video pyramid...")
lap_video = pyramids.build_video_pyramid(video_frames)
amplified_video_pyramid = []
for i, video in enumerate(lap_video):
if i == 0 or i == len(lap_video) - 1:
continue
# Eulerian magnification with temporal FFT filtering
# print("Running FFT and Eulerian magnification...")
result, fft, frequencies = eulerian.fft_filter(video, freq_min,
freq_max, fps)
lap_video[i] += result
# Calculate heart rate
# print("Calculating heart rate...")
heart_rate = heartrate.find_heart_rate(fft, frequencies, freq_min,
freq_max)
print(heart_rate)
return heart_rate
def processing(self,video):
print("processing started")
self.thread_end=False
print(str(len(video))+" initial-framecount")
# lap_video = pyramids.build_video_pyramid(video)
amplified_video_pyramid = []
for i, vide in enumerate(video):
# print(i)
if i == 0 or i == len(video) - 1:
continue
# Eulerian magnification with temporal FFT filtering
# print("Running FFT and Eulerian magnification...")
result, fft, frequencies = eulerian.fft_filter(vide, self.freq_min, self.freq_max, self.fps)
# lap_video[i] += result
print("from heart beat.py", fft)
# Calculate heart rate
# print("Calculating heart rate...")
self.heart_rate = heartrate.find_heart_rate(fft, frequencies, self.freq_min, self.freq_max)
# print(self.heart_rate)
# Collapse laplacian pyramid to generate final video
# print("Rebuilding final video...")
# amplified_frames = pyramids.collapse_laplacian_video_pyramid(lap_video, self.frame_ct)
# Output heart rate and final video
print("Heart rate: ", self.heart_rate, "bpm")
# print("Displaying final video...")
print("processing finished")
self.thread_end = True
self.video_frames.clear()
self.v1.clear()
self.frame_count=0
self.face_detected = False
def processing():
video = []
freq_min = 1
freq_max = 1.8
fps = 30
for i in range(300):
iimg = cv2.imread('Frames/Frame' + str(i) + '.png')
video.append(iimg)
# cv2.imshow('image',video[50])
# Output img with window name as 'image'
# Maintain output window utill
# user presses a key
cv2.waitKey(0)
# time.sleep(5)
# print("processing started")
# print(str(len(video)) + " initial-framecount")
lap_video = pyramids.build_video_pyramid(video)
amplified_video_pyramid = []
for i, video in enumerate(lap_video):
# print(i)
if i == 0 or i == len(lap_video) - 1:
continue
# Eulerian magnification with temporal FFT filtering
# print("Running FFT and Eulerian magnification...")
result, fft, frequencies = eulerian.fft_filter(video, freq_min,
freq_max, fps)
lap_video[i] += result
# Calculate heart rate
# print("Calculating heart rate...")
heart_rate = heartrate.find_heart_rate(fft, frequencies, freq_min,
freq_max)
# Collapse laplacian pyramid to generate final video
# print("Rebuilding final video...")
# amplified_frames = pyramids.collapse_laplacian_video_pyramid(lap_video, self.frame_ct)
# Output heart rate and final video
print(heart_rate)
def __call__(self, source):
self.source = source
print("Reading + pre-processing video...")
if self.ml_model is True:
capture_frames = CaptureFrames()
self.video_frames, self.frame_ct, self.fps = capture_frames(
self.source)
else:
self.video_frames, self.frame_ct, self.fps = read_video(source)
print("Building Laplacian video pyramid...")
self.lap_video = build_video_pyramid(self.video_frames)
amplified_video_pyramid = []
# Eulerian magnification with temporal FFT filtering
print("Running FFT and Eulerian magnification...")
self.result, self.fft, self.frequencies = fft_filter(
self.lap_video[1], self.freq_min, self.freq_max, self.fps)
self.lap_video[1] += self.result
print("Calculating heart rate...")
self.heart_rate = find_heart_rate(self.fft, self.frequencies,
self.freq_min, self.freq_max)
print(self.heart_rate)
if self.final_video:
# Collapse laplacian pyramid to generate final video
print("Rebuilding final video...")
self.amplified_frames = collapse_laplacian_video_pyramid(
self.lap_video, self.frame_ct)
# Output heart rate and final video
print("Heart rate: ", self.heart_rate, "bpm")
if show_frames:
print("Displaying final video...")
for frame in self.amplified_frames:
cv2.imshow("frame", frame)
cv2.waitKey(20)
return self.heart_rate
video_frames, frame_ct, fps = preprocessing.read_video(
"videos/rohin_active.mov")
# Build Laplacian video pyramid
print("Building Laplacian video pyramid...")
lap_video = pyramids.build_video_pyramid(video_frames)
amplified_video_pyramid = []
for i, video in enumerate(lap_video):
if i == 0 or i == len(lap_video) - 1:
continue
# Eulerian magnification with temporal FFT filtering
print("Running FFT and Eulerian magnification...")
result, fft, frequencies = eulerian.fft_filter(video, freq_min, freq_max,
fps)
lap_video[i] += result
# Calculate heart rate
print("Calculating heart rate...")
heart_rate = heartrate.find_heart_rate(fft, frequencies, freq_min,
freq_max)
# Collapse laplacian pyramid to generate final video
print("Rebuilding final video...")
amplified_frames = pyramids.collapse_laplacian_video_pyramid(
lap_video, frame_ct)
# Output heart rate and final video
print("Heart rate: ", heart_rate, "bpm")
print("Displaying final video...")