def store_passage(religion, passage, passage_num, line_index, image_url):
    file_ending = image_url.rpartition('.')[-1]
    out_filenames = ['%s_%s.%s' % (int(time.time() * 1000), i, file_ending) for i in range(3)]
    utils.crop_images(image_url, *[os.path.join(config.IMAGE_DIR, f) for f in out_filenames])
    
    record = {'religion':religion, 'passage':passage, 'passage_num':passage_num, 'selected_line':line_index, 'images':out_filenames}
    db.save(record)
    print record
Пример #2
0
def main():

    if not args.dir:
        from download import download_pascal_voc_2012
        download_pascal_voc_2012()
        args.dir = 'data/VOCdevkit/VOC2012/JPEGImages'

    # load data and crop
    gt = utils.crop_images(args.dir, args.cropping_size, args.samples)
    noise = utils.add_poisson_noise_to_images(gt)

    # scale to [-0.5, 0.5]
    gt_scaled = gt / 255.0 - 0.5
    noise_scaled = noise / 255.0 - 0.5

    del gt
    del noise

    losses, avg_psnr_list = train(gt_scaled, noise_scaled, args.batch_size,
                                  args.learning_rate, args.layers, args.epochs,
                                  args.filters, args.save_path)

    # plot
    _, ax = plt.subplots(ncols=2)
    ax[0].plot(losses)
    ax[1].plot(avg_psnr_list)
    plt.show()
def store_passage(religion, passage, passage_num, line_index, image_url):
    # set defaults if no image was found
    if line_index == '':
        line_index = -1
    if not image_url:
        image_url = default_image

    file_ending = image_url.rpartition('.')[-1]
    out_filenames = ['%s_%s.%s' % (int(time.time() * 1000), i, file_ending) for i in range(3)]
    # saves three copies of the image to the stored_images directory
    utils.crop_images(image_url, *[os.path.join(config.IMAGE_DIR, f) for f in out_filenames])
    # persists the record to the db
    record = {'religion':religion, 'passage':passage, 'passage_num':passage_num, 'selected_line':line_index, 'images':out_filenames}
    try:
        db.save(record)
    except Exception, e:
        print 'An error occurred while saving the record to the db, trying again...'
        db.save(record)
import utils
import configparser

if __name__ == '__main__':
    config = configparser.ConfigParser()
    config.read("config.py")

    prefix = config["DEFAULT"]['prefix']
    input_dir = prefix + config["PLATE_CROPPER"]['input_dir']
    output_dir = prefix + config["PLATE_CROPPER"]['output_dir']
    classified_dir = prefix + config["PLATE_CROPPER"]['classified_dir']

    utils.crop_images(input_dir, output_dir)
    utils.utils.split_into_dirs(classified_dir, input_dir, input_dir)
from keras.callbacks import EarlyStopping, ModelCheckpoint
from skimage.transform import resize, warp, AffineTransform, rotate
from skimage import io, img_as_ubyte
from skimage.util import invert
from matplotlib import pyplot as plt
import random
from cv2 import GaussianBlur

# get train train data
X_train, Y_train = read_train_data()

if 1:
    ix = 2
    img = X_train[ix]
    label = Y_train[ix]
    X_tf, Y_tf = crop_images(X_train, Y_train)

    img_tf = X_tf[ix]
    label_tf = Y_tf[ix]

    plt.figure(figsize=(8, 8))
    plt.subplot(221)
    plt.title('image')
    io.imshow(img)
    plt.subplot(222)
    plt.title('label')
    io.imshow(np.squeeze(label))
    plt.subplot(223)
    plt.title('blur')
    io.imshow(img_tf)
    plt.subplot(224)