def main():
parser = argparse.ArgumentParser(add_help=True)
parser.add_argument('--config', help="Path to config file.")
args, _ = parser.parse_known_args()
configfile = args.config or {'run1': {}}
configs = Config(configfile)
for run in configs:
print("create submission for: ", run)
resultpath = os.path.join(resultspath, run)
if not os.path.exists(resultpath):
os.makedirs(resultpath)
submissionfile = os.path.join(resultpath, 'submission.csv')
if os.path.exists(submissionfile):
os.remove(submissionfile)
# get config for current run
config = configs.get()
backends.set_backend(config['backend'])
# Load Model
modelfile = os.path.join('results/', run, 'model.checkpoint')
model = Model(config, modelfile)
# dataloader
dataloader = DataLoader(config=config, mode='test')
# predictor
predictor = Predictor(model=model,
config=config,
backend=backends.backend())
with open(submissionfile, 'a') as f:
f.write('img,pixels\n')
for index, (img, filename) in enumerate(dataloader):
print('{}/{}'.format(index + 1, len(dataloader)))
mask = predictor.predict(img)
mask = cv2.resize(
mask, (config['orig_width'], config['orig_height']),
interpolation=cv2.INTER_NEAREST)
save = False
if save:
imgfile = os.path.join(
resultpath,
os.path.basename(filename).split(".")[0] + ".png")
cv2.imwrite(imgfile, mask * 255)
enc = run_length_enc(mask)
f.write('{},{}\n'.format(
os.path.basename(filename).split(".")[0],
' '.join(map(str, enc))))
sys.exit(0)
def main():
parser = argparse.ArgumentParser(add_help=True)
parser.add_argument('--config', help="Path to config file.")
args, _ = parser.parse_known_args()
configfile = args.config or {'run1': {}}
configs = Config(configfile)
for run in configs:
print("Run: ", run)
resultpath = os.path.join(resultspath, run)
if not os.path.exists(resultpath):
os.makedirs(resultpath)
configs.save(resultpath + '/config.yml')
# get config for current run
config = configs.get()
# set backend
backends.set_backend(config['backend'])
# summary
summarywriter = backends.backend().get_summary_writer(
logdir=resultpath)
# Load Model
modelfile = os.path.join('results/', run, 'model.checkpoint')
model = Model(config, modelfile)
# augmentation
augmentation = Augmentation(config=config)
# data loader
dataloader = DataLoader(config=config,
mode='train',
augmentation=augmentation)
# validation data loader
valdataloader = DataLoader(config=config, mode='val')
trainer = Trainer(config,
model,
dataloader,
valdataloader=valdataloader,
summarywriter=summarywriter)
trainer.train()
report = Report(configs, resultspath)
report.generate()
sys.exit(0)
from protoseg import Report
from protoseg import HyperParamOptimizer
from protoseg import backends
resultspath = 'results/'
def help():
return "Config file parameter missing. Run like: python train.py /path/to/config.yml 100, where 100 is max_evals."
if __name__ == "__main__":
max_evals = 10
if len(sys.argv) < 2:
print(help())
sys.exit(1)
configs = Config(sys.argv[1])
if len(sys.argv) > 2:
max_evals = int(sys.argv[2])
report = Report(configs, resultspath)
for run in configs:
print("Run: ", run)
resultpath = os.path.join(resultspath, run)
if not os.path.exists(resultpath):
os.makedirs(resultpath)
configs.save(resultpath + '/config.yml')
# get config for current run
config = configs.get()
# set backend
backends.set_backend(config['backend'])
# summary
def test_len():
config = Config(configs=configs)
assert(len(config), 2)
def test_iterator():
count = 0
config = Config(configs=configs)
for _ in config:
count += 1
assert(count, 2)
def test_index():
config = Config(configs=configs)
assert(config[0], 'run1')
assert(config[1], 'run2')
length = end - start
res = [[s + 1, l + 1] for s, l in zip(list(start), list(length))]
res = list(chain.from_iterable(res))
return res # ' '.join([str(r) for r in res])
def help():
return "Config file parameter missing. Run like: python submit.py /path/to/config.yml"
if __name__ == "__main__":
if len(sys.argv) < 2:
print(help())
sys.exit(1)
configs = Config(sys.argv[1])
for run in configs:
print("create submission for: ", run)
resultpath = os.path.join(resultspath, run)
if not os.path.exists(resultpath):
os.makedirs(resultpath)
submissionfile = os.path.join(resultpath, 'submission.csv')
if os.path.exists(submissionfile):
os.remove(submissionfile)
# get config for current run
config = configs.get()
backends.set_backend(config['backend'])
# summary
summarywriter = backends.backend().get_summary_writer(