a96bf92790895e2f1a83ce9f9fbc7cbca38fb5b3,examples/convolutional_lstm.py,,,#,2

Before Change

print("Collecting data...")
csv_file_path = "image_data/sample.csv"
imageProcessor = ImageProcessor(from_csv=True, target_labels=target_labels, datapath=csv_file_path, target_dimensions=target_dimensions, raw_dimensions=raw_dimensions, csv_label_col=0, csv_image_col=1, channels=1)
images, labels = imageProcessor.get_training_data()
if verbose:
	print ("images shape: " + str(images.shape))

print("Extracting features...")

After Change

print("Processing data...")
imageProcessor = ImageProcessor(images, target_dimensions=target_dimensions, rgb=False, channels=1)
images = imageProcessor.process_training_data()
if verbose:
	print ("processed image shape: " + str(images.shape))

print("Extracting features...")
featureExtractor = FeatureExtractor(images, return_2d_array=True)
featureExtractor.add_feature("hog", {"orientations": 8, "pixels_per_cell": (16, 16), "cells_per_block": (1, 1)})
raw_features = featureExtractor.extract()

Instances