error while parsing dataset
manthanSoriya opened this issue · 2 comments
while running cvs_to_numpy.py I encountered this error. Can someone help me with it?
for index, row in data.iterrows():
emotion = emotion_to_vec(row['emotion'])
image = data_to_image(row['pixels'])
if image is not None:
labels.append(emotion)
images.append(image)
#labels.append(emotion)
#images.append(flip_image(image))
else:
print "Error"
index += 1
print "Progreso: {}/{} {:.2f}%".format(index, total, index * 100.0 / total)
inside this for loop I don't understand why execution goes into this else case. Because of this else case error is occurring while data parsing
(48, 48)
Progreso: 1/35887 0.00%
Error
Progreso: 2/35887 0.01%
(48, 48)
Progreso: 3/35887 0.01%
Error
Progreso: 4/35887 0.01%
(48, 48)
Progreso: 5/35887 0.01%
(48, 48)
Progreso: 6/35887 0.02%
Error
Progreso: 7/35887 0.02%
(48, 48)
Progreso: 8/35887 0.02%
(48, 48)
Progreso: 9/35887 0.03%
(48, 48)
Progreso: 10/35887 0.03%
(48, 48)
Progreso: 11/35887 0.03%
Error
Progreso: 12/35887 0.03%
Error
Progreso: 13/35887 0.04%
Error
Progreso: 14/35887 0.04%
(48, 48)
Progreso: 15/35887 0.04%
(48, 48)
Progreso: 16/35887 0.04%
Error
Progreso: 17/35887 0.05%
Error
Progreso: 18/35887 0.05%
Error
Progreso: 19/35887 0.05%
Error
Progreso: 20/35887 0.06%
Error
Progreso: 21/35887 0.06%
Error
Progreso: 22/35887 0.06%
(48, 48)
Progreso: 23/35887 0.06%
Error
Progreso: 24/35887 0.07%
Error
Progreso: 25/35887 0.07%
(48, 48)
Progreso: 26/35887 0.07%
Error
Progreso: 27/35887 0.08%
Error
Progreso: 28/35887 0.08%
Error
Progreso: 29/35887 0.08%
Error
Progreso: 30/35887 0.08%
(48, 48)
Progreso: 31/35887 0.09%
Error
Progreso: 32/35887 0.09%
Error
Progreso: 33/35887 0.09%
(48, 48)
Progreso: 34/35887 0.09%
Error
Progreso: 35/35887 0.10%
(48, 48)
Progreso: 36/35887 0.10%
(48, 48)
Progreso: 37/35887 0.10%
(48, 48)
Progreso: 38/35887 0.11%
(48, 48)
Progreso: 39/35887 0.11%
Error
Progreso: 40/35887 0.11%
(48, 48)
Progreso: 41/35887 0.11%
(48, 48)
Progreso: 42/35887 0.12%
Error
@manthanSoriya I think this is problem in the built in algorithm of face detection. The algorithm of open CV is not so good. when that algo did not detect image an error is shown in training .. :)
The comment of @NomiMalik0207 is correct. When OpenCV can't find a face I just skip it. Also the quality of the dataset is not perfect.