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)