oneoneliu/ggcnn_cornell_dataset

cornell grasp dataset analyses and process

ggcnn_cornell_dataset's Issues

jacquard dataset数据集

About Cornell Grasping Dataset

Hello, because the Cornell Grasping Dataset link is invalid, do you have any files you can provide to me? Thank you

Hi,friend!!

Could I ask you one question?What is the address where you download this cornell dataset?I can't log on to the previous website.

如何去预测单张图片

hello,大佬，我想用您的代码去预测单张图片的抓取点，请问在您的基础上如何修改，感谢！！！

Question on the difference between the definition of length and width

Hello, when comparing your code with that of dougsm https://github.com/dougsm/ggcnn, I found that both of you predict width instead of length.

As you've mentioned in your code, the definition of length and width is different in your code from that of dougsm. Did he make a mistake？This question also bothers me a long time.

您好，我想请问一下，做测试的时候，如何将640*480的深度图处理，转为网络的输入（原文中300*300）

关于抓取仿真的问题

朋友你好，我看到了在baxter-pnp你给我的关于配置仿真环境的回复，我现在也没有成功，也是在学习阶段的一个新手，能加个联系方式一起交流吗

关于出视频？

你好，我是在学习了您这个代复现的笔记，目前正在学习，我的想法是 想在此基础上出一些视频教程，版权我会注明，不知您是否同意？

大佬，请问为什么制作标签的时候要取三分之一？为什么角度限制在-90到90？

角度范围-180到180不可以吗？为什么求正余弦要对角度的两倍求，直接原角度求正余弦再arctan2反求角度不行吗（前提角度限定范围在-180，180）？
还有刚试了试把标签当作网络输出去验证，不知道为什么都不匹配
`
import torch
import torch.optim as optim
import numpy as np
import matplotlib.pyplot as plt
import cv2
import time

#导入自定义包
from ggcnn import GGCNN
from cornell_pro import Cornell
from functions import post_process,detect_grasps,max_iou
from image_pro import Image
from grasp_pro import Grasp_cpaw

val_data = Cornell('图片标签路径',
random_rotate = True,
random_zoom = True,
output_size = 300)
val_dataset = torch.utils.data.DataLoader(val_data,batch_size = 1,shuffle = True)
for x,y,idx,rot,zoom in val_dataset:
q_out,ang_out,width_out = post_process(y[0], y[1], y[2], y[3])
grasps_pre = detect_grasps(q_out,ang_out,width_out,no_grasp = 1)
grasps_true = val_dataset.dataset.get_raw_grasps(idx,rot,zoom)

result = 0
for grasp_pre in grasps_pre:
    if max_iou(grasp_pre,grasps_true) > 0.25:
        result = 1
        break

if result==0:
    print(val_dataset.dataset.graspf[idx])
    #break

`

Question about the definition of axis X and Y in the code

Hello, I am confused by the aixs X and Y in the function as_gr.

def as_gr(self):
    """
    Convert to GraspRectangle
    :return: GraspRectangle representation of grasp.
    """
    xo = np.cos(self.angle)
    yo = np.sin(self.angle)

    y1 = self.center[0] + self.length / 2 * yo
    x1 = self.center[1] - self.length / 2 * xo
    y2 = self.center[0] - self.length / 2 * yo
    x2 = self.center[1] + self.length / 2 * xo

    return GraspRectangle(np.array(
        [
         [y1 - self.width/2 * xo, x1 - self.width/2 * yo],
         [y2 - self.width/2 * xo, x2 - self.width/2 * yo],
         [y2 + self.width/2 * xo, x2 + self.width/2 * yo],
         [y1 + self.width/2 * xo, x1 + self.width/2 * yo],
         ]
    ).astype(np.float))

The definition of axis X and Y is different for images and in mathsmatics. Does the code use the definition in mathsmatics instead of in imgae in the code above?