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Add return object when creating h5py dataset to check integrity #736

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Add return object when creating h5py dataset to check integrity #736

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14 changes: 11 additions & 3 deletions tflearn/data_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -371,8 +371,8 @@ class containing the images to classify.
assert mode in ['folder', 'file'], "`mode` arg must be 'folder' or 'file'"

if mode == 'folder':
images, labels = directory_to_samples(target_path,
flags=files_extension)
images, labels, classes = directory_to_samples(target_path,
flags=files_extension)
else:
with open(target_path, 'r') as f:
images, labels = [], []
Expand Down Expand Up @@ -416,6 +416,9 @@ class containing the images to classify.
else:
dataset['Y'][i] = labels[i]

return H5pyDataset(classes, image_shape, image_count)


def get_img_channel(image_path):
"""
Load a image and return the channel of the image
Expand Down Expand Up @@ -744,7 +747,7 @@ def directory_to_samples(directory, flags=None, filter_channel=False):
samples.append(os.path.join(c_dir, sample))
targets.append(label)
label += 1
return samples, targets
return samples, targets, classes


# ==================
Expand Down Expand Up @@ -843,6 +846,11 @@ def preload(self, label, n_class, categorical_label):
else:
return label

class H5pyDataset(object):
def __init__(self, classes, image_shape, image_count):
self.classes = classes
self.image_shape = image_shape
self.image_count = image_count

def get_max(X):
return np.max(X)
Expand Down