Fixed bug in video frame rate in MAHNOB database file.

README.md

@@ -146,7 +146,7 @@ The framework contains the implementation of many common methods for remote-PPG
 |PCA      | Lewandowska, M., Rumiński, J., Kocejko, T., & Nowak, J. (2011, September). Measuring pulse rate with a webcam—a non-contact method for evaluating cardiac activity. In 2011 federated conference on computer science and information systems (FedCSIS) (pp. 405-410). IEEE.|
 |POS      | Wang, W., den Brinker, A. C., Stuijk, S., & de Haan, G. (2016). Algorithmic principles of remote PPG. IEEE Transactions on Biomedical Engineering, 64(7), 1479-1491.|
 |SSR      | Wang, W., Stuijk, S., & De Haan, G. (2015). A novel algorithm for remote photoplethysmography: Spatial subspace rotation. IEEE transactions on biomedical engineering, 63(9), 1974-1984.|
-|OMIT     | Álvarez Casado, C., Bordallo López, M. (2022). Face2PPG: An unsupervised pipeline for blood volume pulse extraction from faces. arXiv (eprint 2202.04101).|
+|OMIT     | Álvarez Casado, C., & Bordallo López, M. (2023). Face2PPG: An unsupervised pipeline for blood volume pulse extraction from faces. IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2023.3307942.|
 |MTTS-CAN | Liu, X., Fromm, J., Patel, S., & McDuff, D. (2020). Multi-task temporal shift attention networks for on-device contactless vitals measurement. Advances in Neural Information Processing Systems, 33, 19400-19411.|
 |HR-CNN   | Spetlik, R., Franc, V., Cech, J. and Matas, J. (2018). Visual Heart Rate Estimation with Convolutional Neural Network. In Proceedings of British Machine Vision Conference|
 
@@ -157,17 +157,17 @@ Currently supported datasets are:
 
 | Dataset name |                              Link                                      |
 | ------------ | ---------------------------------------------------------------------- |
-| COHFACE    | https://www.idiap.ch/dataset/cohface |
-| LGI-PPGI   | https://github.com/partofthestars/LGI-PPGI-DB |
-| MAHNOB-HCI | https://mahnob-db.eu/hci-tagging/ |
-| PURE       | https://www.tu-ilmenau.de/neurob/data-sets-code/pulse-rate-detection-dataset-pure|
-| UBFC1      | https://sites.google.com/view/ybenezeth/ubfcrppg|
-|UBFC2       | https://sites.google.com/view/ybenezeth/ubfcrppg|
-|UBFC-Phys   | https://sites.google.com/view/ybenezeth/ubfc-phys|
-|ECG-Fitness | https://cmp.felk.cvut.cz/~spetlrad/ecg-fitness/*
-|Vicar-PPG-2 | https://docs.google.com/forms/d/e/1FAIpQLScwnW_D5M4JVovPzpxA0Bf1ZCTaG5vh7sYu48I0MVSpgltvdw/viewform*
-|V4V         | https://vision4vitals.github.io/ |
-|VIPL-HR     |https://arxiv.org/abs/1810.04927 |
+| COHFACE     | https://www.idiap.ch/dataset/cohface |
+| LGI-PPGI    | https://github.com/partofthestars/LGI-PPGI-DB |
+| MAHNOB-HCI  | https://mahnob-db.eu/hci-tagging/ |
+| PURE        | https://www.tu-ilmenau.de/neurob/data-sets-code/pulse-rate-detection-dataset-pure|
+| UBFC1       | https://sites.google.com/view/ybenezeth/ubfcrppg|
+| UBFC2       | https://sites.google.com/view/ybenezeth/ubfcrppg|
+| UBFC-Phys   | https://sites.google.com/view/ybenezeth/ubfc-phys|
+| ECG-Fitness | https://cmp.felk.cvut.cz/~spetlrad/ecg-fitness/*
+| Vicar-PPG-2 | https://docs.google.com/forms/d/e/1FAIpQLScwnW_D5M4JVovPzpxA0Bf1ZCTaG5vh7sYu48I0MVSpgltvdw/viewform*
+| V4V         | https://vision4vitals.github.io/ |
+| VIPL-HR     |https://arxiv.org/abs/1810.04927 |
 
 
 

pyVHR/datasets/cohface.py

@@ -31,7 +31,7 @@ class COHFACE(Dataset):
     numLevels = 2            # depth of the filesystem collecting video and BVP files
     numSubjects = 40         # number of subjects
     video_EXT = 'avi'        # extension of the video files
-    frameRate = 20           # vieo frame rate
+    frameRate = 20           # video frame rate
     VIDEO_SUBSTRING = 'data'  # substring contained in the filename
     SIG_EXT = 'hdf5'         # extension of the BVP files
     SIG_SUBSTRING = 'data'   # substring contained in the filename

pyVHR/datasets/ecg_fitness.py

@@ -34,8 +34,8 @@ class ECG_FITNESS(Dataset):
     frameRate = 20       # video frame rate
     VIDEO_SUBSTRING = ''  # substring contained in the filename
     SIG_EXT = 'csv'     # extension of the ECG files
-    SIG_SUBSTRING = 'viatom' # substring contained in the filename
-    SIG_SampleRate = 120 # sample rate of the ECG files
+    SIG_SUBSTRING = 'viatom'  # substring contained in the filename
+    SIG_SampleRate = 120  # sample rate of the ECG files
 
     def readSigfile(self, filename):
         """ Load ECG signal.

pyVHR/datasets/lgi_ppgi.py

@@ -26,7 +26,7 @@ class LGI_PPGI(Dataset):
     numLevels = 2             # depth of the filesystem collecting video and BVP files
     numSubjects = 4           # number of subjects
     video_EXT = 'avi'         # extension of the video files
-    frameRate = 25            # vieo frame rate
+    frameRate = 25            # video frame rate
     VIDEO_SUBSTRING = 'cv_camera'  # substring contained in the filename
     SIG_EXT = 'xml'           # extension of the BVP files
     SIG_SUBSTRING = 'cms50'   # substring contained in the filename

pyVHR/datasets/mahnob.py

@@ -12,6 +12,7 @@
 
 """
 
+
 class MAHNOB(Dataset):
     """
     Mahnob Dataset
@@ -27,15 +28,15 @@ class MAHNOB(Dataset):
     ..     |...
     """
     name = 'MAHNOB'
-    signalGT = 'ECG'     # GT signal type
-    numLevels = 2        # depth of the filesystem collecting video and BVP files
-    numSubjects = 40     # number of subjects
-    video_EXT = 'avi'    # extension of the video files
-    frameRate = 20       # video frame rate
+    signalGT = 'ECG'  # GT signal type
+    numLevels = 2  # depth of the filesystem collecting video and BVP files
+    numSubjects = 40  # number of subjects
+    video_EXT = 'avi'  # extension of the video files
+    frameRate = 61  # video frame rate
     VIDEO_SUBSTRING = 'Section'  # substring contained in the filename
-    SIG_EXT = 'bdf'     # extension of the ECG files
-    SIG_SUBSTRING = 'emotion' # substring contained in the filename
-    SIG_SampleRate = 256 # sample rate of the ECG files
+    SIG_EXT = 'bdf'  # extension of the ECG files
+    SIG_SUBSTRING = 'emotion'  # substring contained in the filename
+    SIG_SampleRate = 256  # sample rate of the ECG files
 
     def readSigfile(self, filename):
         """ Load ECG signal.
@@ -49,4 +50,3 @@ def readSigfile(self, filename):
         self.SIG_SampleRate = bdfRec.sampRate[33]
         data = np.array(rec['data'][0])[rec['eventTable']['idx'][2]:]
         return ECGsignal(data, self.SIG_SampleRate)
-

pyVHR/datasets/pure.py

@@ -7,6 +7,7 @@
 import re
 import cv2
 
+
 class PURE(Dataset):
     """
     PURE Dataset
@@ -30,15 +31,15 @@ class PURE(Dataset):
     ..     |...
     """
     name = 'PURE'
-    signalGT = 'BVP'      # GT signal type
-    numLevels = 1         # depth of the filesystem collecting video and BVP files
-    numSubjects = 10      # number of subjects
-    video_EXT = 'avi'     # extension of the video files ### IMPORTANT NOTE: pure datasets consists of a sequence of png files, we converted them in a video avi files
-    frameRate = 30.0        # vieo frame rate
+    signalGT = 'BVP'  # GT signal type
+    numLevels = 1  # depth of the filesystem collecting video and BVP files
+    numSubjects = 10  # number of subjects
+    video_EXT = 'avi'  # extension of the video files ### IMPORTANT NOTE: pure datasets consists of a sequence of png files, we converted them in a video avi files
+    frameRate = 30.0  # video frame rate
     VIDEO_SUBSTRING = '-'  # substring contained in the filename
-    SIG_EXT = 'json'      # extension of the BVP files
-    SIG_SUBSTRING = '-'   # substring contained in the filename
-    SIG_SampleRate = 60   # sample rate of the BVP files
+    SIG_EXT = 'json'  # extension of the BVP files
+    SIG_SUBSTRING = '-'  # substring contained in the filename
+    SIG_SampleRate = 60  # sample rate of the BVP files
     skinThresh = [40, 60]  # thresholds for skin detection
 
     def readSigfile(self, filename):
@@ -65,23 +66,23 @@ def loadFilenames(self):
         """
 
         if self.name not in self.videodataDIR:
-            if self.videodataDIR[-1]=='/':
+            if self.videodataDIR[-1] == '/':
                 self.videodataDIR += self.name
             else:
                 self.videodataDIR = self.videodataDIR + '/' + self.name
 
         print(self.videodataDIR)
-        #check if video files exist or create them from images
+        # check if video files exist or create them from images
         for root, dirs, files in os.walk(self.videodataDIR):
             for d in dirs:
                 dirname = os.path.join(root, d)
-                if not glob.glob(dirname +'/*.avi'):
-                    #create videofile from images
+                if not glob.glob(dirname + '/*.avi'):
+                    # create videofile from images
                     frames = self.__loadFrames(dirname)
                     fps = self.frameRate
                     width = frames[0].shape[1]
                     height = frames[0].shape[0]
-                    #fourcc = cv2.VideoWriter_fourcc(*'MPNG')
+                    # fourcc = cv2.VideoWriter_fourcc(*'MPNG')
                     writer = cv2.VideoWriter(dirname + '/' + d + '.avi', 0, fps, (width, height))
                     for frame in frames:
                         writer.write(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
@@ -101,12 +102,12 @@ def loadFilenames(self):
         # -- number of videos
         self.numVideos = len(self.videoFilenames)
 
-    def __sort_nicely(self, l): 
+    def __sort_nicely(self, l):
         """ Sort the given list in the way that humans expect. 
-        """ 
-        convert = lambda text: int(text) if text.isdigit() else text 
-        alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ] 
-        l.sort( key=alphanum_key )
+        """
+        convert = lambda text: int(text) if text.isdigit() else text
+        alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key)]
+        l.sort(key=alphanum_key)
         return l
 
     def __loadFrames(self, directorypath):
@@ -116,6 +117,6 @@ def __loadFrames(self, directorypath):
         for n in range(len(f_names)):
             filename = os.path.join(directorypath, f_names[n])
             frames.append(cv2.imread(filename)[:, :, ::-1])
-        
+
         frames = np.array(frames)
         return frames

pyVHR/datasets/ubfc1.py

@@ -22,7 +22,7 @@ class UBFC1(Dataset):
     numLevels = 2        # depth of the filesystem collecting video and BVP files
     numSubjects = 8     # number of subjects
     video_EXT = 'avi'    # extension of the video files
-    frameRate = 30       # vieo frame rate
+    frameRate = 30       # video frame rate
     VIDEO_SUBSTRING = ''  # substring contained in the filename
     SIG_EXT = 'xmp'     # extension of the BVP files
     SIG_SUBSTRING = ''  # substring contained in the filename

pyVHR/datasets/ubfc2.py

@@ -22,7 +22,7 @@ class UBFC2(Dataset):
     numLevels = 2        # depth of the filesystem collecting video and BVP files
     numSubjects = 26     # number of subjects
     video_EXT = 'avi'    # extension of the video files
-    frameRate = 30       # vieo frame rate
+    frameRate = 30       # video frame rate
     VIDEO_SUBSTRING = 'vid'  # substring contained in the filename
     SIG_EXT = 'txt'     # extension of the BVP files
     SIG_SUBSTRING = ''  # substring contained in the filename

pyVHR/datasets/ubfc_phys.py

@@ -22,7 +22,7 @@ class UBFC_PHYS(Dataset):
     numLevels = 2        # depth of the filesystem collecting video and BVP files
     numSubjects = 56     # number of subjects
     video_EXT = 'avi'    # extension of the video files
-    frameRate = 35       # vieo frame rate
+    frameRate = 35       # video frame rate
     VIDEO_SUBSTRING = ''  # substring contained in the filename
     SIG_EXT = 'csv'     # extension of the BVP files
     SIG_SUBSTRING = 'bvp'  # substring contained in the filename

pyVHR/datasets/v4v.py

@@ -22,7 +22,7 @@ class V4V(Dataset):
     numLevels = 2        # depth of the filesystem collecting video and BVP files
     numSubjects = 56     # number of subjects
     video_EXT = 'mkv'    # extension of the video files
-    frameRate = 25       # vieo frame rate
+    frameRate = 25       # video frame rate
     VIDEO_SUBSTRING = ''  # substring contained in the filename
     SIG_EXT = 'txt'     # extension of the BVP files
     SIG_SUBSTRING = 'BP'  # substring contained in the filename

pyVHR/datasets/vicar_ppg.py

@@ -22,7 +22,7 @@ class VICAR_PPG(Dataset):
     numLevels = 2        # depth of the filesystem collecting video and BVP files
     numSubjects = 40     # number of subjects
     video_EXT = 'mp4'    # extension of the video files
-    frameRate = 60       # vieo frame rate
+    frameRate = 60       # video frame rate
     VIDEO_SUBSTRING = ''  # substring contained in the filename
     SIG_EXT = 'csv'     # extension of the BVP files
     SIG_SUBSTRING = ''  # substring contained in the filename

pyVHR/datasets/vipl_hr_v1.py

@@ -22,7 +22,7 @@ class VIPL_HR_V1(Dataset):
     numLevels = 2  # depth of the filesystem collecting video and BVP files
     numSubjects = 107  # number of subjects
     video_EXT = 'avi'  # extension of the video files
-    frameRate = 30  # vieo frame rate
+    frameRate = 30  # video frame rate
     VIDEO_SUBSTRING = 'video'  # substring contained in the filename
     SIG_EXT = 'csv'  # extension of the BVP files
     SIG_SUBSTRING = 'wave'  # substring contained in the filename