'/home/nicoli/github/alexnet/dataset/csv/imdb_csv/imdb_age_regression.csv',
index_col=0)
# In[3]:
cols = list(df.columns[1:])
in_format = list(df.columns)
# In[9]:
train_dataset = BatchGenerator(box_output_format=cols)
validation_dataset = BatchGenerator(box_output_format=cols)
train_dataset.parse_csv(
labels_filename=
'/home/nicoli/github/alexnet/dataset/csv/imdb_csv/imdb_age_regression_train_split_47950-70-10-20.csv',
images_dir='/home/nicoli/github/alexnet/dataset/imdb-hand-crop/',
input_format=in_format)
validation_dataset.parse_csv(
labels_filename=
'/home/nicoli/github/alexnet/dataset/csv/imdb_csv/imdb_age_regression_val_split_47950-70-10-20.csv',
images_dir='/home/nicoli/github/alexnet/dataset/imdb-hand-crop/',
input_format=in_format)
# In[10]:
img_height, img_width, img_depth = (224, 224, 3)
epochs = 100
in_format = list(df.columns)
cols, in_format
# In[6]:
train_dataset = BatchGenerator(box_output_format=cols)
validation_dataset = BatchGenerator(box_output_format=cols)
train_dataset. parse_csv(labels_filename='dataset/csv/imdb_csv/imdb_age_regression_train_split_47950-70-10-20.csv',
images_dir='dataset/imdb-hand-crop',
input_format=in_format)
validation_dataset.parse_csv(labels_filename='dataset/csv/imdb_csv/imdb_age_regression_val_split_47950-70-10-20.csv',
images_dir='dataset/imdb-hand-crop',
input_format=in_format)
# In[7]:
img_height, img_width, img_depth = (224,224,3)
epochs = 1000
train_batch_size = 64
shuffle = True
ssd_train = False
validation_batch_size = 32
# In[2]:
activations = ['relu', 'lrelu']
img_treats = ['image-treat-1', 'image-treat-2', 'image-treat-3']
nets = ['lenet', 'alexnet']
for img_treat in img_treats:
for net in nets:
for activation in activations:
# In[3]:
test_dataset = BatchGenerator(box_output_format=['class_id'])
test_dataset.parse_csv(
labels_filename=
'/home/nicoli/github/alexnet/dataset/csv/imdb_csv/imdb_age_regression_test_split_47950-70-10-20.csv',
images_dir=
'/home/nicoli/github/alexnet/dataset/imdb-hand-crop/',
input_format=['image_name', 'class_id'])
# In[4]:
print("Number of images in the dataset:",
test_dataset.get_n_samples())
# In[5]:
img_height, img_width, img_depth = (224, 224, 3)
#epochs = 90
batch_size = 100