FVNet is proposed for 3D object front-view proposal generation and detection from point cloud
Previous coarse research paper: FVNet
This just is my graduation project, and I will complete it gradually. I promise. ^_^
FVNet is proposed for 3D object front-view proposal generation and detection from point cloud
FVNet is proposed for 3D object front-view proposal generation and detection from point cloud
Previous coarse research paper: FVNet
This just is my graduation project, and I will complete it gradually. I promise. ^_^
The same in log_train.txt:
**** EPOCH 999 ****
2019-12-20 01:50:44.774636
-- 400 / 429 --
mean total loss: 4238.088100
mean center loss: 1508.271276
mean stage1 center loss: 2049.937858
mean angle class loss: 1.753821
mean angle res loss: 0.164341
mean size res loss: 4.236634
mean corners loss: 118.021132
box IoU (ground/3D): 0.000000 / 0.000000
box estimation accuracy (IoU=0.5): 0.000000
box estimation accuracy (IoU=0.7): 0.000000
**** EPOCH 1000 ****
2019-12-20 01:51:33.322000
-- 400 / 429 --
mean total loss: 4242.318448
mean center loss: 1517.564768
mean stage1 center loss: 2046.396386
mean angle class loss: 1.752404
mean angle res loss: 0.164301
mean size res loss: 4.221072
mean corners loss: 117.779481
box IoU (ground/3D): 0.000000 / 0.000000
box estimation accuracy (IoU=0.5): 0.000000
box estimation accuracy (IoU=0.7): 0.000000
2019-12-20 01:52:21.722286
---- EPOCH 199 EVALUATION ----
eval mean total loss: 7092.537344
eval mean center loss: 2995.654283
eval mean stage1 center loss: 2896.207265
eval mean angle class loss: 1.749893
eval mean angle res loss: 0.164299
eval mean size res loss: 4.265863
eval mean corners loss: 222.064536
eval box IoU (ground/3D): 0.000000 / 0.000000
eval box estimation accuracy (IoU=0.5): 0.000000
eval box estimation accuracy (IoU=0.7): 0.000000
Model saved in file: /home/FVNet/est-kittinet/outputs/20191219100152/model_1000.ckpt
The process is successful and not warning.
Are there some operations I ignore?
In kitti_dataset.py
Line11: lidar_dir = data_dir + "/cropped/"
Line26: pc_velo_path = self.lidar_dir + img_id + ".npy"
Line27: pc_velo = np.load(pc_velo_path)
Should I use np.fromfile() to load KITTI dataset /training/velodyne data which is ".bin" file?
I don't know what the cropped directory contains. Could you tell me, please? Thanks a lot.
I have successfully run preprocess_car_person.py, and generated the .npy in cropped directory.
But while I run train.py, it still has a problem like this:
/root/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py:2957: RuntimeWarning: Mean of empty slice.
out=out, **kwargs)
/root/anaconda3/lib/python3.6/site-packages/numpy/core/_methods.py:73: RuntimeWarning: invalid value encountered in true_divide
ret, rcount, out=ret, casting='unsafe', subok=False)
Traceback (most recent call last):
File "train.py", line 385, in
train()
File "train.py", line 195, in train
train_one_epoch(sess, ops, train_writer)
File "train.py", line 235, in train_one_epoch
get_batch(TRAIN_DATASET, train_idxs, start_idx, end_idx, NUM_CHANNEL)
File "/home/FVNet/est-kittinet/kitti/kitti_dataset.py", line 113, in get_batch
sample = dataset[idxs[(i + start_idx) % num]]
File "/home/FVNet/est-kittinet/kitti/kitti_dataset.py", line 47, in getitem
replace=(object_rect.shape[0] < self.num_point))
File "mtrand.pyx", line 1120, in mtrand.RandomState.choice
ValueError: a must be greater than 0
Do you have met the problem before? Should I normalize some data? Hope for help, thanks.
As a novice, during learning your codes, I have found the implementing functions of PE-Net module, such as get_center_regression_net(), get_3d_box_estimation_net() in front_pointnets_v1.py. But I totally can't find the implementing functions of PG-Net. Could you give me some hints? Thanks a lot!
I've read your paper: FVNet, and I eagerly want to get much more information from your README to run your code and see some results, pls.
Could you commit the list_files, such as det_train_car_filtered.txt, label_train_2_car_filtered.txt. Thank you!
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