Comments (1)
BlueDing101
commented on July 28, 2024
1
You only need to remove all the part of reading ground true from json file, and pass your original image and bounding boxes to the test_net() function. The predict_one() function in the test_net() is the feed forward function.
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Related Issues (20)
- Has anyone tested on the MPII dataset?
- Strange results HOT 1
- About detect single person HOT 16
- About code running environment
- How do I test with pictures?
- bbox is necessary in Test? HOT 2
- An error occurred after I executed： `python3 mptest.py -d 0-1 -m log/model_dump/snapshot_350.ckpt`
- global_loss += tf.reduce_mean(tf.square(global_out - global_label)) / len(labels); global_loss /= 2;.so damn hard to understand
- why? gk15 = (23, 23) gk11 = (17, 17) gk9 = (13, 13) gk7 = (9, 9)
- strange results
- > @dagongji10 Excuse me, can I ask you a question? Must I provide bbox of pictures when I test a picture?Could you please give me a script which can visualize test results like what you show? Thank you very much HOT 3
- coco dataset? which year?
- train train
- "read none image" during training? HOT 1
- from nets.basemodel import resnet50, resnet_arg_scope, resnet_v1
- labels = [label15, label11, label9, label7]
- How to apply inference on own dataset without GT_bbox(.json)?
- How to decrease Batch size HOT 4
- Using just GlobalNet
- is it possible to add new joint in the skel and retrain the model
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