tnikolla/robot-grasp-detection

Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.

robot-grasp-detection's Issues

about pretraining on imagenet

There are some limits for me to pretrain on imagenet. Can I get the pretrained model? Many thanks!

what is the rectangle metric detection accuracy

Hi,

I have a question in the paper(Real-Time Grasp Detection Using Convolutional Neural Networks).
In the table I , what's the rectangle metric detection accuracy? and how to compute the value?
I search many paper, they don't have explanation.

thanks.

Hi, author

Excuse me,

What is the meaning "in filename[:49] adapt the number 49 (you can contribute, or I will program it better someday)"?

About the models

Hi, I am wondering whether the grasp model is the one pretrained on the imagenet? Can I use it to train the trainset? I tried , but the loss is nan?

may i ask how to make my own dataset?

I want to train my own model,and make the dataset by myself,but i don't know what the format is and want some help,thanks!

error when run grap_det.py

when I run grasp_det.py, I met this error as follow:
ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float64: 'Tensor("truediv:0", shape=(), dtype=float64, device=/device:CPU:0)'
How can I solve this error?????

I had used "build_cgd_dataset.py" to get tfrecords.

I has made small changes in "grasp_det.py" as follow:

TRAIN_FILE = r'F:\RGB-D_grasp_datasets\data01\01\train-cgd'
VALIDATE_FILE = r'F:\RGB-D_grasp_datasets\data01\01\validation-cgd'

parser.add_argument(
'--data_dir',
type=str,
default=r'F:\RGB-D_grasp_datasets\data01\01',
help='Directory with training data.'
)
parser.add_argument(
'--log_dir',
type=str,
default=r'F:\robot-grasp-detection-master',
help='Tensorboard log_dir.'
parser.add_argument(
'--model_path',
type=str,
default=r'F:\robot-grasp-detection-master\models\grasp\m4.ckpt',
help='Variables for the model.'
)

About ImageNet

Training Parameter about grasp

Hi ,I try to test the code and want to get the same result.
But I do not know the training parameter you didi with grasp_det.py, could you tell me the exact parameters ?

About multiplication factors 0.35 & 0.47

Hi author,

In your program, there are values: 0.35 and 0.47. What do they mean?

Thank you!

def bboxes_to_grasps(bboxes): # converting and scaling bounding boxes into grasps, g = {x, y, tan, h, w} box = tf.unstack(bboxes, axis=1) #bboxes <tf.Tensor 'batch_join:1' shape=(64, 8) dtype=float32> x = (box[0] + (box[4] - box[0])/2) *0.35 y = (box[1] + (box[5] - box[1])/2) *0.47 tan = (box[3] -box[1]) / (box[2] -box[0]) *0.47/0.35 h = tf.sqrt(tf.pow((box[2] -box[0])*0.35, 2) + tf.pow((box[3] -box[1])*0.47, 2)) w = tf.sqrt(tf.pow((box[6] -box[0])*0.35, 2) + tf.pow((box[7] -box[1])*0.47, 2)) return x, y, tan, h, w

Where is your code which finds the grasp point

I am the new hand to learn the grasp detection. I don't know how to run the code, and i can't find the code which to find the grasp point.

I am new to tensorflow and CNN, how can I predict a grasp of a image using existing model, it seems that this repository only include training code, thank you.

How to convert the coordinates

Hi, I've achieved the grasping rectangle on my Jupiter notebook. But I want to use a real robotic arm to grasp item, I knew that inverse kinematics can convert the coordinates of the arm into the rotation angle of different parts of the arm. But I realize that the coordinates systems are different, in your project, it's based on the image, while in practice it's based on the robotic arm. How can I convert the system to make it work? Thanks a lot.

I want to know how much the last loss

Hello
Run grab_det.py, after 10000 steps, the loss is stable at 30000-40000, and how much is the reasonable loss!

working with D435 cam realtime

HI, thank you for your project,
I want to use it with D435 Cam in real time, how can i modify anything to use your project in realtime with cam D435? thank you so much.

do I need to download all the imageset dataset?

Converting grasping rectangle to grasp pose

Hi, I wish to execute the proposed grasp using my own robot arm. I am wondering if you have implemented the code to convert the rectangle to the 6DOF grasp pose.
I read on the Deep Learning for Detecting Robotic Grasps paper that the final pose is determined using the rectangle center as the grasping center, its surface normal as the approach vector and the angle of the rectangle is used to rotate the gripper around the approach vector but I don't know how to implement this.

About Regression + Classification and Pretraining

Hi！
In paper 'Real-Time Grasp Detection Using Convolutional Neural Networks'
part IV. GRASP DETECTION WITH NEURAL NETWORKS
C. Regression + Classification
D. MultiGrasp Detection
Do you have a program?
part V. EXPERIMENTS AND EVALUATION
C. Pretraining
Is models/imagenet/m2/m2.ckpt the weight of pre-training results saved？
or models/imagenet/m4/m4.ckpt
Thank you！
Shu Guo！

Why the training process take up 100% CPU?

Hi, Why the training process takes up 100% CPU?
Does the calling the function distorted_inputs() cause that?

imagenet_classifier.py

1.please excuse me output this "2021-06-21 15:36:13.057525: I C:\tf_jenkins\workspace\rel-win\M\windows\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2" is succeed???
2.'Done training for 100 epochs, 0 steps, 0.0 min.' what's wrong? thank you!

New to tensorflow and TFRecords - error in running build_cd_dataset.py

I seem to get this error:
I'm using Spyder/Anaconda with Python 3.6
f.read() jsut doesn't seem to like opening images

File "C:/Users/Elijah/Desktop/Masters and Machine Learning folder/Cornell Dataset/robot-grasp-detection-master/build_cgd.py", line 31, in _process_image
image_data = f.read()

File "C:\Users\Elijah\Anaconda3\envs\mle_gpu\lib\encodings\cp1252.py", line 23, in decode
return codecs.charmap_decode(input,self.errors,decoding_table)[0]

UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 50: character maps to

Any help would be appreciated, thanks

Rectangular four vertex law

Hi!
I thought for a long time on this issue, did not think clearly
Rectangular four vertex law is not a law, such as clockwise, counterclockwise, or where the first vertex, these will not affect the results?
This function:
def bboxes_to_grasps(bboxes):
box = tf.unstack(bboxes, axis=1)
x = (box[0] + (box[4] - box[0])/2) * 0.35
y = (box[1] + (box[5] - box[1])/2) * 0.47
tan = (box[3] -box[1]) / (box[2] -box[0]) *0.47/0.35
h = tf.sqrt(tf.pow((box[2] -box[0])*0.35, 2) + tf.pow((box[3] -box[1])*0.47, 2))
w = tf.sqrt(tf.pow((box[6] -box[0])*0.35, 2) + tf.pow((box[7] -box[1])*0.47, 2))
return x, y, tan, h, w
Thank you!

When I run grasp_det.py for the training on pycharm, some errors happened

Hi!
When I run grasp_det.py for the training on pycharm, there were some errors,

/home/xiaoshuguo/anaconda3/bin/python /home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_det.py
validation
inputs
False
False
Traceback (most recent call last):
File "/home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_det.py", line 162, in
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/home/xiaoshuguo/anaconda3/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(sys.argv[:1] + flags_passthrough))
File "/home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_det.py", line 115, in main
run_training()
File "/home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_det.py", line 47, in run_training
images, bboxes = grasp_img_proc.inputs([data_files])
File "/home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_img_proc.py", line 158, in inputs
num_readers=1)
File "/home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_img_proc.py", line 122, in batch_inputs
image_buffer, bbox = parse_example_proto(examples_serialized)
File "/home/xiaoshuguo/PycharmProjects/untitled2/robot-grasp-detection/grasp_img_proc.py", line 26, in parse_example_proto
r = 8*tf.random_uniform((1,), minval=0, maxval=tf.size(bboxes, out_type=tf.int32)/8, dtype=tf.int32)
File "/home/xiaoshuguo/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/random_ops.py", line 229, in random_uniform
maxval = ops.convert_to_tensor(maxval, dtype=dtype, name="max")
File "/home/xiaoshuguo/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 639, in convert_to_tensor
as_ref=False)
File "/home/xiaoshuguo/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 704, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/home/xiaoshuguo/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 577, in _TensorTensorConversionFunction
% (dtype.name, t.dtype.name, str(t)))
ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float64: 'Tensor("truediv:0", shape=(), dtype=float64, device=/device:CPU:0)'

I don't know why it is?
How can I resovle it?
Thank you very much! #

Where is inference_redmon.py

Hi, I downloaded the codes several days ago, but I can't find the 'inference_redmon.py' file in the directory. So where is it?

Trying to implement validation on grasp_det.py

Traceback (most recent call last):
File "build_cgd_dataset.py", line 115, in
main()
File "build_cgd_dataset.py", line 97, in main
image_buffer, height, width = _process_image(filename, coder)
File "build_cgd_dataset.py", line 29, in _process_image
image_data = f.read()
File "/home/harsh/anaconda3/envs/py36/lib/python3.6/codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte

I want to know what models files are

Hi!

I want to know what models files are,and how can I use them?

Thank you very much!

may i ask if i train the model,should i use RGB-D images or just RGB images?

hello,i have read the paper(Real-Time Grasp Detection Using Convolutional Neural Networks),and the paper saied that uses the RGB-D image to train the model,and may i ask the code in this project,should i use RGB-D images or RGB images ,or both of them is ok?thank you very much, this problem is very important to me!!

datasets

Hi , how do you splits Cornell dataset on image-wise and object-wise? Thanks!

I have problems when trainning on grasping dataset after obtainning the train_file and validate_file

/robot-grasp-detection-master$ python grasp_det.py
train
distorted_inputs
True
True
pass
keep_prob = 1.0
2018-01-29 14:48:20.935569: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-29 14:48:20.935592: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-29 14:48:20.935613: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-01-29 14:48:20.935632: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-29 14:48:20.935637: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "grasp_det.py", line 164, in
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "grasp_det.py", line 117, in main
run_training()
File "grasp_det.py", line 113, in run_training
coord.join(threads)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/coordinator.py", line 389, in join
six.reraise(*self._exc_info_to_raise)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/queue_runner_impl.py", line 238, in _run
enqueue_callable()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1063, in _single_operation_run
target_list_as_strings, status, None)
File "/usr/lib/python2.7/contextlib.py", line 24, in exit
self.gen.next()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.FailedPreconditionError: /home/zhaojie/zhaojie/robot-grasp-detection-master
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](TFRecordReaderV2, input_producer)]]

Multiple bboxes, positive and negative bboxes?

It seems only the positive bounding boxes might be loaded, is this the case?

Also, how are the varying numbers of bboxes handled / structured?

The code for that part is split in several locations so it isn't easy to tell the design.

downloading the code

how large is the downloaded cofe file? is it around 16mb ? i m unable to download the code .please help

This network only works on the object of the image center?

I used other images to test it and found that this network only works on the object of the image center!!!

Why is it like this?

Thank you!
Shu Guo

Could you add a LICENSE.md?

@tnikolla this repository looks very useful thanks for putting it up!

Would you mind adding a license to this? Without a license it is impossible to legally clone or run this code. If you're not sure and would like a suggestion the Apache 2.0 license is a good option. A quick summary of apache 2.0 is available at tl;dr legal. This is the same license used by TensorFlow. Here is the license text:

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How can I transfer this project to python3, it seems this project is writen in python2, thank you.

About depth information

Hi,

The article you mentioned "Real-time Grasp Detection..." has the image depth information included when training the CNN. While the title of your repository "robot-grasp-detection" is "Detecting grasping... using RGB images".

Does it mean when training your network, you only used RGB images, and depth info. is not used ?
Further, the Cornell Grasping Dataset, has point cloud information of all images. If your network is trained with this dataset, depth information should be included. Am I correct ?
Thanks.

ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float64: 'Tensor("truediv:0", shape=(), dtype=float64, device=/device:CPU:0)'

May I ask how to solve this problem? Thanks, I've been working on it for a long time!

grasp_det.py

ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float64: 'Tensor("truediv:0", shape=(), dtype=float64, device=/device:CPU:0)'

May I ask how to solve this problem？

ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float64: 'Tensor("truediv:0", shape=(), dtype=float64, device=/device:CPU:0)'

    ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float64: 'Tensor("truediv:0", shape=(), dtype=float64, device=/device:CPU:0)'

May I ask how to solve this problem? Thanks, I've been working on it for a long time!

Originally posted by @zhoumo1121 in #22 (comment)