goldsborough commented 6 years ago

Hi, thank you for your contribution. It seems the tests are still failing, unfortunately. Could you make them pass? Thanks.

24hours commented 6 years ago

The failed tests are style related. I have no idea how to style numpy matrix and make pep8 happy. I turned off some pep 8 check finally to pass the test. I am not sure if that is the best solution.

codecov-io commented 6 years ago

Codecov Report

Merging #110 into master will increase coverage by 11.83%. The diff coverage is 100%.

@@             Coverage Diff             @@
##           master     #110       +/-   ##
===========================================
+ Coverage   66.14%   77.97%   +11.83%     
===========================================
  Files          22       22               
  Lines         824      840       +16     
===========================================
+ Hits          545      655      +110     
+ Misses        279      185       -94

Impacted Files	Coverage Δ
keras_rcnn/layers/losses/_rpn.py	`95.91% <ø> (+61.22%)`	:arrow_up:
keras_rcnn/backend/tensorflow_backend.py	`96.22% <ø> (+7.54%)`	:arrow_up:
keras_rcnn/layers/losses/_rcnn.py	`96.61% <100%> (+55.23%)`	:arrow_up:
keras_rcnn/layers/pooling.py	`100% <100%> (+69.44%)`	:arrow_up:
keras_rcnn/layers/detection.py	`85.71% <100%> (ø)`	:arrow_up:
keras_rcnn/preprocessing/_object_detection.py	`16.17% <0%> (-17.79%)`	:arrow_down:
keras_rcnn/backend/common.py	`92.46% <0%> (+1.36%)`	:arrow_up:
...s_rcnn/layers/object_detection/_object_proposal.py	`95.55% <0%> (+51.11%)`	:arrow_up:
... and 2 more

Continue to review full report at Codecov.

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0x00b1 commented 6 years ago

Thanks, @24hours! Fantastic work.

Would you mind adding yourself to the contributors file in the root directory?

broadinstitute / keras-rcnn

Fix some test case due to out dated code #110

Codecov Report