philip-huang / pixor Goto Github PK
View Code? Open in Web Editor NEWPyTorch Implementation of PIXOR
License: MIT License
PyTorch Implementation of PIXOR
License: MIT License
The 3d locations of ground truth boxes are in camera coordinate. In this implementation, coordinate transformation of 3d locations just contains rotation transformation. Is the translation ignored? And in rotation transformation, I think "z=-z" is necessary, which is similar to "y=-y" in datagen.py
What changes are needed to be made to the code for training on multiple classes including pedestrian and truck?
Hi,
I started training PIXOR your implementation with a Batch_size=1.
I trained upto 40 epoch as mentioned in the code. Loaded the checkpoint 34 from trained model.
It seems that after training num_pred=0 i.e number of predictions boxes becomes zero.
Loss curves are behaving well.
Kindly provide solution if you have solved it.
1.The score of the prediction is too low.if I need to modify the alpha and beta?
2.And how should I set the object_list and filter the train dataset to make the balance of positive and negetive data?
3.I meet the problem like others in compute_iou():float divided by zero.How to avoid it?
If you have any ideas,welcome
pls,thank you
Hi, I tried to run this program on my computer, and when I executed the following command:
python main.py train --name=default
I got this error:
AttributeError: module 'tensorboard.summary._tf.summary' has no attribute 'FileWriter'
this is the detail:
Using device cpu
There are 3712 images in txt file
Found 3712 Velodyne scans...
done.
There are 3769 images in txt file
Found 3769 Velodyne scans...
done.
------------------------------------------------------------------
Traceback (most recent call last):
File "main.py", line 395, in <module>
train(args.name, device)
File "main.py", line 191, in train
train_logger = get_logger(config, 'train')
File "/home/andre/masterarbeit/PIXOR/srcs/utils.py", line 57, in get_logger
return logger.Logger(folder)
File "/home/andre/masterarbeit/PIXOR/srcs/logger.py", line 15, in __init__
self.writer = tf.summary.FileWriter(log_dir)
AttributeError: module 'tensorboard.summary._tf.summary' has no attribute 'FileWriter'
the version of tensorflow is 2.1. Can you tell me how to solve this problem? thx
After traiing for round 40 epoch with batchsize=1,
On validation/testing kitti dataset, vehcile bounding box won't get detected. Hence this repository is useless since after training, i didn't got anyresult. Henve i conclude that this repository doesn't work properly
Also multi-gpu with batch-size=1, model doesn't trained and crashes?
Poor training and no results after running the code .
Hi Philip,
This repository looks great :)
Would you mind adding an open-source license? Otherwise it could be problematic for other people to use it.
Best,
Martin
Hi,
I didn't found any concept of anchor in detecting vehicles and also IOU calculation and NMS threshold. Can you pls give better insight?
Why this implementtaion does not use focal loss for per column class loss ? It seems to use straight cross enthropy, despite the prevalence of negative samples.
@yanghuan478 @czha5168 sorry for the lately update
Even when I am using batch size of 1, still cuda out of memory error is coming. Any suggestions?
Hi, man, I try your method and I often meet the problem "num_pred=0" in function "compute_ap", and this problem always leads to training process interrupt. Do you meet the same problem?
Hi
I trained your PIXOR network for 40 epoch with decrease in loss curves.
How when i execute python main.py --mode=val --name=default , the below error occurs.. Kindly help please
Traceback (most recent call last):
File "/usr/lib/python3.5/multiprocessing/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/usr/lib/python3.5/multiprocessing/pool.py", line 47, in starmapstar
return list(itertools.starmap(args[0], args[1]))
File "/home/Tracking/PIXOR-master/srcs/postprocess.py", line 129, in filter_pred
selected_ids = non_max_suppression(corners, scores, config['nms_iou_threshold'])
File "/home/Tracking/PIXOR-master/srcs/postprocess.py", line 96, in non_max_suppression
iou = compute_iou(polygons[i], polygons[ixs[1:]])
File "/home/Tracking/PIXOR-master/srcs/postprocess.py", line 51, in compute_iou
iou = [box.intersection(b).area / box.union(b).area for b in boxes]
File "/home/Tracking/PIXOR-master/srcs/postprocess.py", line 51, in
iou = [box.intersection(b).area / box.union(b).area for b in boxes]
ZeroDivisionError: float division by zero
Kindly suggest what is the functionality of trasform_label2metric?
HI
I would like to know that the results of this repo are comparable to the results reported by the paper
Thanks
How to run the program in real time on ros system
Hi, do you know what dataset is used exactly? There are many parts of the KITTI Bird's Eye View dataset. I don't know which should I download. Thank you.
Bird's Eye View Evaluation 2017:
Download left color images of object data set (12 GB)
Download right color images, if you want to use stereo information (12 GB)
Download the 3 temporally preceding frames (left color) (36 GB)
Download the 3 temporally preceding frames (right color) (36 GB)
Download Velodyne point clouds, if you want to use laser information (29 GB)
Download camera calibration matrices of object data set (16 MB)
Download training labels of object data set (5 MB)
Hi,
Thanks for sharing code. We got BEV results in terms of 2D. But to use 2D bounding box results on 3D pointcloud bounding boxes. Kindly help
Runing average time:
Average Preprocessing Time: 0.096s
Forward Time: 0.011s
Postprocessing Time: 0.073s
Preprocessing time cost too much, morethtan even forward time.....
Hi, how to training multi class at the same time?
Are the Calib files in the kitti dataset not used for transformation from 2D to 3D coordinates?
I am using one GPU to train the model, but it is still using around 10-16G CPU memory. Would you please tell what operations are using so much memory on the CPU.
Hi.
I downloaded synced+rectified 2011_09_26_drive_0005 dataset along with calibration file from
http://www.cvlibs.net/datasets/kitti/raw_data.php
Call me noob but I am unable to train on kitti dataset. Instruction says run
$: python srcs/main.py train (--name=$exp_name$)
But what should exp_name be for the above Kitti dataset be?
How do you calculate the standard mean and deviation for bounding box sizes for multiple classes, or for training on your own dataset.
In datagen.py:
def get_corners(self, bbox):
w, h, l, y, z, x, yaw = bbox[8:15]
y = -y
the bbox[8] is width, bbox[9] is height and bbox[10] is length. But in KITTI's instruction (readme.txt in devkit_object.zip), bbox[8] is height, bbox[9] is width and bbox[10] is length.
In loss.py shouldn't line 85
loss = loss(pred, label)
be
loss = loss.forward(pred, label)
Thank you for your great job!
Could you please share a pretrained model for testing?
Hi,
I trained pixor with a batch-size 1 and run for around35 epoch. Loss was exponentially decreasing.
With that trained model when i started evaluated using python main.py --mode=test --name=default or python main.py --mode=val --name=default, iam getting no prediction boxes.
I trained with batchsize1 using 1080Ti since for larger batch_size>=4, the code was crashing.
Kindly help me/suggest me in getting correct prediction boxes. Pls help
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