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…tion tensor needs to be broadcast
Hey @Zha0q1 , Thanks for submitting the PR
CI supported jobs: [windows-cpu, unix-cpu, sanity, windows-gpu, centos-gpu, miscellaneous, unix-gpu, clang, website, centos-cpu, edge] Note: |
@@ -240,14 +238,20 @@ def obj_detection_test_images(tmpdir_factory): | |||
'faster_rcnn_resnet101_v1d_coco', | |||
'yolo3_darknet53_coco', | |||
'yolo3_mobilenet1.0_coco', | |||
'mask_rcnn_resnet18_v1b_coco', |
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By adding the mask_rcnn under obj_detection tests, we are not testing the segmentation part?
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I think the mask is a little hard to test numerically since they can be different across mxnet and onnxruntime
@@ -199,8 +199,6 @@ def obj_detection_test_images(tmpdir_factory): | |||
tmpdir = tmpdir_factory.mktemp("obj_det_data") | |||
from urllib.parse import urlparse | |||
test_image_urls = [ | |||
'https://github.com/apache/incubator-mxnet-ci/raw/master/test-data/images/car.jpg', | |||
'https://github.com/apache/incubator-mxnet-ci/raw/master/test-data/images/duck.jpg', |
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Why do we remove the images here?
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Those two images would fail the maskrcnn models. It's not like maskrcnn models do not work on them, but they would output slightly different boxes than mxnet
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LGTM, thanks!
Fixes 6 maskrcnn models
TODO: add model tests