b8f005eebd686c3e16b3a3603f294db0013a569e,src/predict.py,,,#,47
Before Change
sys.stdout.flush()
if os.path.isfile(out_file):
continue
pred = predict(segmenter, imfile, target_shape=(dw, dh))
res = cv2.imwrite(out_file, pred)
print("")
After Change
mode = "opencv"
filetxt = sys.argv[1] // txt with image filenames
pw = sys.argv[2] // pretrained weights
out_directory = sys.argv[3] // output directory
// dw = 256
// dh = 256
// dw = None
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 4
Instances
Project Name: PavlosMelissinos/enet-keras
Commit Name: b8f005eebd686c3e16b3a3603f294db0013a569e
Time: 2017-04-07
Author: pmelissi@iti.gr
File Name: src/predict.py
Class Name:
Method Name:
Project Name: scikit-learn-contrib/DESlib
Commit Name: bba1901f835525551dde9ec1537d041abc88d293
Time: 2021-04-08
Author: rafaelmenelau@gmail.com
File Name: deslib/static/oracle.py
Class Name: Oracle
Method Name: predict
Project Name: EpistasisLab/tpot
Commit Name: 3b07e9f94047f9e22548f3a8783296efc3cea10f
Time: 2016-08-12
Author: bartleyn@uchicago.edu
File Name: tpot/operators/classifiers/base.py
Class Name: Classifier
Method Name: _train_and_predict