kitti-object-eval-python
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Fast kitti object detection eval in python(finish eval in less than 10 second)
here is my code : for confidence in range(1,10): label_filename = "./evaluate/label_2" result_path="./results/exp%d"%49 split_file = "./evaluate/lists/val.txt" print(0.9+confidence/100) evaluate(label_filename, result_path, split_file,score_thresh=0.9+confidence/100) output: 0.91 Car AP(Average Precision)@0.70, 0.70, 0.70: bbox AP:27.05, 23.71,...
Excuse me, how to calculate the score parameters required in the code
Line https://github.com/traveller59/kitti-object-eval-python/blob/master/eval.py#L277 only applies the nstuff filter when metric =0 i.e; evaluating on image 2D bbbox. The current implementation gives poor performance when evaluation is done through bev or 3D...
Something wrong in calculate_iou_partly,and I dont know how to fix it. File "/workspace/OpenPCDet-master/pcdet/datasets/kitti/kitti_dataset.py", line 363, in evaluation ap_result_str, ap_dict = kitti_eval.get_official_eval_result(eval_gt_annos, eval_det_annos, class_names) File "/workspace/OpenPCDet-master/pcdet/datasets/kitti/kitti_object_eval_python/eval.py", line 675, in get_official_eval_result gt_annos,...
#bug: Incorrect threshold values are inserted
Hello, this error occurred when I was running, I don’t know where the problem is, I hope I can get help.Thank u.  numba.core.errors.TypingError: Failed in nopython mode pipeline (step:...
In the official benchmark, for cars the overlap is supposed to be 70%. Which line corresponds to the official benchmark as given [here](http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d)?
I redivided the KITTI training to train and val, about 7:3. But when i eval the network. I found my result so low. I also see the result txt. I...
I am sure that skimage, numpy, fire, numba and scipy is ready in my python environment, and I have already fired 'conda install -c numba cudatoolkit=10.0' according to my cuda...
Hi there, many thanks for sharing this code! I'm new to Kitti and I just successfully ran the code on my detection result. However, I don't quite understand the result...