FactorizableNet
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yikang-li
Factorizable Net (Multi-GPU version): An Efficient Subgraph-based Framework for Scene Graph Generation
/home/prudhvik/FactorNet/FactorizableNet/data/VRD/images/sg_test_images/161638840_4de67b36c9_o.jpg use_gt_boxes=args.use_gt_boxes) File "/home/prudhvik/FactorNet/FactorizableNet/models/HDN_v2/engines_v1.py", line 123, in test for i, sample in enumerate(loader): # (im_data, im_info, gt_objects, gt_relationships) File "/home/prudhvik/anaconda/envs/py2/lib/python2.7/site-packages/torch/utils/data/dataloader.py", line 637, in __next__ return self._process_next_batch(batch) File "/home/prudhvik/anaconda/envs/py2/lib/python2.7/site-packages/torch/utils/data/dataloader.py", line 658,...
In evaluate stage,predict boxes and ground truth boxes are used to compute a iou score to retain reasonable boxes.But what to do without ground truth?
Hi, Thanks for publicizing the code and it is really well-written. However, there seems to a minor prpblem related to evaluating object detection result. In train_FN.py, there is no reference...
First of all thanks for the repository. I have some queries hope they get answered soon. 1) - How to run code to generate scene graph for a single test-image....
the order is CUDA_VISIBLE_DEVICES=0 python train_FN.py --evaluate_object \ --path_opt options/models/VRD.yaml \ --pretrained_model output/best_model_4.h5 ========== Testing ======= ============ Done ============ Done dumping to: output/FN_VRD_2_iters_SGD/evaluate_object_detection Evaluating... Traceback (most recent call last): File...
File "train_FN.py", line 400, in main() File "train_FN.py", line 279, in main use_gt_boxes=args.use_gt_boxes) File "/home/swf/F-Net/models/HDN_v2/engines_v1.py", line 133, in test use_gt_boxes=use_gt_boxes) File "/home/swf/F-Net/models/HDN_v2/factorizable_network_v4.py", line 280, in evaluate object_result, predicate_result = self.forward_eval(im_data,...
In figure3， it shows the avg-pooled features(m × 515×1×1),but it didn't dot product 1*512. Is the number 515 wrong? 512??
But in the figure2(3), the subgraph has contained three object. But the below only refers to two object. So could the subgraph merged from three objects be computed by three...