Comments (6)
This is your example I was referring to (from the other repository):
from tf-faster-rcnn.
Hi, the lion prediction was made without the nms.
If you remove the non max suppression method, sort the predictions according to the probabilities and draw the first few results, you can get similar results.
from tf-faster-rcnn.
Or you can try my last update.
I made the change mentioned above in rpn predictor.
from tf-faster-rcnn.
With the latest update I got these (with a clean pulled master branch). All boxes are starting from upper left:
Doing a quick print of the selected_rpn_bboxes tensor gives values between 1 and 10:
From the TF docs it seems expected values should be between 0 and 1:
Should I try to retrain my model or I'm missing something?
Model is trained with rpn_trainer.py, mobilenet_v2 and voc/2007.
from tf-faster-rcnn.
Hi, your results already range from 0 to 1.
We can simply say that your model is not well trained.
When your model is sufficiently trained, you should get similar results below.
from tf-faster-rcnn.
Ok, I'll train it again for 100 epochs and for voc2012.
Thanks a lot!
from tf-faster-rcnn.
Related Issues (20)
- HOW to train my own dataset? HOT 1
- ValueError: Dimension 2 in both shapes must be equal, but are 4 and 1. Shapes are [?,1500,4] and [?,1500,1]. for '{{node roi_deltas/Select_1}} = Select[T=DT_FLOAT](roi_deltas/ExpandDims_9, roi_deltas/GatherV2_1, roi_deltas/zeros_like_1)' with input shapes: [?,1500,1], [?,1500,4], [?,1500,4].
- No such file or directory
- Training strategy HOT 1
- Erorr in reg_loss HOT 13
- 请问作者,voc2007和voc2012数据集训练时是怎么存放的?
- 怎么指定自己的VOC数据集
- ValueError: The two structures don't have the same sequence length. Input structure has length 0, while shallow structure has length 9. HOT 3
- Is there a trained checkpoint or weight h5 file?
- Question about epochs and learning rate selection
- Predict Error HOT 1
- Data Request
- variances in train_utils.py
- Bounding box resizing in preprocessing??
- Error occurred when finalizing GeneratorDataset iterator
- 数据集下载 HOT 3
- ValueError: The two structures don't have the same sequence length. Input structure has length 0, while shallow structure has length 9. HOT 3
- ValueError: The two structures don't have the same sequence length. Input structure has length 0, while shallow structure has length 9. HOT 1
- Does it support multi-GPU training? HOT 1
- ValueError: Dimension 2 in both shapes must be equal, but are 4 and 1. Shapes are [?,1500,4] and [?,1500,1]. for 'roi_deltas/Select' (op: 'Select') with input shapes: [?,1500,1], [?,1500,4], [?,1500,4]. HOT 1
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from tf-faster-rcnn.