POSITIVE_IMAGE_DIR = os.path.join('data/Flickr_2800', args.pos_class)
# let the user know what we're up to
log.log("Training " + IDENTIFIER + " FROM " + POSITIVE_IMAGE_DIR)
if args.transplant is not None:
log.log("(Starting from " + args.transplant + "_t" + args.lesion_indicator + ")")
else:
log.log("(Starting from <blank net, random weights>)")
# train it all
with AlexNet() as alexnet:
# Load data
log.log("[Loading Data...]")
all_data = Data()
all_data.load_images(POSITIVE_IMAGE_DIR, POSITIVE_LABEL)
all_data.load_images('data/Flickr_2800/notall', NEGATIVE_LABEL)
train_data, test_data = all_data.split_train_test(train_split=0.90)
# Initialize net
if args.transplant is not None:
load_transplant_dir = os.path.join(TRANSPLANT_DIR, args.transplant + '.ckpt')
alexnet.load_transplant(load_transplant_dir)
if args.lesion_indicator is not '':
layers = [i for i, e in enumerate(args.lesion_indicator) if e == '0']
alexnet.lesion_layers(layers)
# Train
log.log("[Training...]")
i = 0
from lib.alexnet import AlexNet
from lib.data import Data
from lib.perf import Perf
import lib.utils as utils
import matplotlib.pyplot as plt
import lib.log as log
import numpy as np
import argparse
import os
# constants
IMAGES_DIR = 'data/Flickr_2800'
# actual run
if __name__ == "__main__":
# parse args out
parser = argparse.ArgumentParser()
parser.add_argument("img_class",
type=str,
help="The directory from Flickr_2800 to plot")
parser.add_argument("x", type=int, help="Columns")
parser.add_argument("y", type=int, help="Rows")
args = parser.parse_args()
d = Data()
d.load_images(os.path.join(IMAGES_DIR, args.img_class), None)
d.graph(args.x, args.y)
plt.show()
from lib.alexnet import AlexNet
from lib.data import Data
from lib.perf import Perf
import lib.utils as utils
import matplotlib.pyplot as plt
import lib.log as log
import numpy as np
import argparse
import os
# constants
IMAGES_DIR = 'data/Flickr_2800'
# actual run
if __name__ == "__main__":
# parse args out
parser = argparse.ArgumentParser()
parser.add_argument("img_class", type=str, help="The directory from Flickr_2800 to plot")
parser.add_argument("x", type=int, help="Columns")
parser.add_argument("y", type=int, help="Rows")
args = parser.parse_args()
d = Data()
d.load_images(os.path.join(IMAGES_DIR, args.img_class), None)
d.graph(args.x, args.y)
plt.show()
