test_vid_class = classify_library.get_vid_class(args.test_list, index_class,
args.dataset)
training = [
filename for filename in os.listdir(training_output)
if filename.endswith('.fisher.npz')
]
testing = [
filename for filename in os.listdir(testing_output)
if filename.endswith('.fisher.npz')
]
print(training[:5])
print(testing[:5])
print(train_vid_class.keys()[:5])
training_dict = classify_library.toDict(training, train_vid_class)
testing_dict = classify_library.toDict(testing, test_vid_class)
#GET THE TRAINING AND TESTING DATA.
X_train_vids = classify_library.limited_input1(training_dict,
args.per_class_num)
X_test_vids = classify_library.limited_input1(testing_dict, args.per_class_num)
# X_train_vids, X_test_vids = classify_library.limited_input(training_dict, testing_dict, 101, 24)
X_train, Y_train = classify_library.make_FV_matrix(X_train_vids,
training_output,
class_index,
train_vid_class)
X_test, Y_test = classify_library.make_FV_matrix(X_test_vids, testing_output,
class_index, test_vid_class)
# In[7]:
training_output = '../data/fishers/train'
testing_output = '../data/fishers/test'
training = [
filename for filename in os.listdir(training_output)
if filename.endswith('.fisher.npz')
]
testing = [
filename for filename in os.listdir(testing_output)
if filename.endswith('.fisher.npz')
]
training_dict = classify_library.toDict(training)
testing_dict = classify_library.toDict(testing)
####################################################################
####################################################################
################################## Script starts
X_train_vids = classify_library.limited_input1(training_dict, 1000)
X_test_vids = classify_library.limited_input1(testing_dict, 1000)
#GET THE TRAINING AND TESTING DATA.
X_train, Y_train = classify_library.make_FV_matrix(X_train_vids,
training_output,
class_index)
X_test, Y_test = classify_library.make_FV_matrix(X_test_vids,
testing_output,
class_index_file = "/Users/Bryan/CS/CS_Research/code/CS221/class_index.npz"
class_index_file_loaded = np.load(class_index_file)
class_index = class_index_file_loaded['class_index'][()]
index_class = class_index_file_loaded['index_class'][()]
# In[7]:
training_output = '/Users/Bryan/CS/CS_Research/code/CS221/UCF101_Fishers/train'
testing_output = '/Users/Bryan/CS/CS_Research/code/CS221/UCF101_Fishers/test'
training = [filename for filename in os.listdir(training_output) if filename.endswith('.fisher.npz')]
testing = [filename for filename in os.listdir(testing_output) if filename.endswith('.fisher.npz')]
training_dict = classify_library.toDict(training)
testing_dict = classify_library.toDict(testing)
####################################################################
####################################################################
################################## Script starts
X_train_vids = classify_library.limited_input1(training_dict, 1000)
X_test_vids = classify_library.limited_input1(testing_dict, 1000)
#GET THE TRAINING AND TESTING DATA.
X_train, Y_train = classify_library.make_FV_matrix(X_train_vids,training_output, class_index)
