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...")