detr | End-to-End Object Detection with Transformers | Computer Vision library
kandi X-RAY | detr Summary
kandi X-RAY | detr Summary
DE⫶TR: End-to-End Object Detection with Transformers.
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Top functions reviewed by kandi - BETA
- Evaluate a model
- Summarize metrics
- Combine common COCs
- Synchronize between two COCs
- Perform the prediction
- Resize an image
- Interpolate input tensor
- Compute the cost matrices
- Convert box coordinates to x coordinates
- Calculates the loss for each box
- Compute the model
- Reduce a dictionary
- Build a model for resnet50
- Detect resnet101
- Compute the loss for each label
- Build a Resnet50 model
- Build a Resnet101 model
- Forward the prediction
- Forward computation
- Compute the prediction
- Get argument parser
- Perform the forward computation
- Forward the forward projection
- Train one epoch
- Compute loss masks
- Plot log files
detr Key Features
detr Examples and Code Snippets
Lines of Code : 54License : Permissive (Apache-2.0)
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├── model # DETR模型相关的python代码(主要来源[1].https://github.com/facebookresearch/detr)
│ ├── README.md
│ ├── __init__.py
│ ├── backbone.py # backbone resnet50
│ ├── box_ops.py
│ ├── detr.py # pytorch to onnx
$ python3 detr_pth2onnx.py -h
# batch_size=1, static
# 在项目下生成detr.onnx和detr_sim.onnx(simplify后的onnx)
$ python3 detr_pth2onnx.py --model_dir ./checkpoint/detr_resnet50.pth --check --onnx_dir ./detr.onnx
# dynamic shape
# 在项目下生成det # 提供build engine和反序列化engine进行推断
# inference_detr_trt.py支持FP32,FP16的build engine和engine的推断，同时支持static shape和Dynamic shape的推断，前处理，后处理和结果可视化，支持INT8量化后engine的推断，包括static shape, dynamic shape及前处理后处理和结果可视化
# static shape
# FP32
$ python3 inference_detr_tr Community Discussions
Trending Discussions on detr
QUESTION
Hi (and apologies for the long message)
I have a use-case that seems fairly common and on which I bang my head.
I am using FastAPI to serve some ML models and I have a Streamlit basic UI using python-requests.
One of my service is getting an image through a POST request and it is working like a charm.
fastapi
...ANSWER
Answered 2022-Mar-09 at 12:27To pass query parameters in Python requests, you should use params key instead. Hence:
QUESTION
For my model, I load pretrained version of DetrFeatureExtractor:
...ANSWER
Answered 2022-Feb-03 at 10:12Your values to the constructor are not taken, because you are calling .from_pretrained(), which loads all values from the respective config file of the pretrained model (in your case, the corresponding config file can be viewed here).
Even if some values might not be specified in the config, they will be primarily taken from the default values, instead of whatever you're passing before.
If you want to change attributes, you can do so after loading:
QUESTION
Goal: Amend this Notebook to work with Albert and Distilbert models
Kernel: conda_pytorch_p36. I did Restart & Run All, and refreshed file view in working directory.
Error occurs in Section 1.2, only for these 2 new models.
For filenames etc., I've created a variable used everywhere:
...ANSWER
Answered 2022-Jan-13 at 14:10When instantiating AutoModel, you must specify a model_type parameter in ./MRPC/config.json file (downloaded during Notebook runtime).
List of model_types can be found here.
Code that appends model_type to config.json, in the same format:
QUESTION
I'm working using Mmdetection to train a Deformable DETR model using a custom COCO Dataset. Meaning a Custom Dataset using the COCO format of annotations. The dataset uses the same images as the COCO with different "toy" annotations for a "playground" experiment and the annotation file was created using the packages pycocotools and json exclusively.
I have made five variations of this playground dataset: 2 datasets with three classes (classes 1, 2, and 3), 1 dataset with six classes (classes 1 to 6) and 2 datasets with 7 classes (classes 1 to 7).
Now, after creating the dataset in mmdetection using mmdet.datasets.build_dataset, I used the following code to check if everything was OK:
ANSWER
Answered 2021-Sep-23 at 15:47There was a mismatch between the classes names in the annotation file and the classes names in the mmdetection config object. Correcting those solved the problem.
QUESTION
def forward(self, src,
mask: Optional[Tensor] = None,
src_key_padding_mask: Optional[Tensor] = None,
pos: Optional[Tensor] = None):
output = src
ANSWER
Answered 2021-May-08 at 13:51Optional is used for type hints. Please refer to this from the Python docs.
Typing was introduced in Python 3.5. It does not affect your run time, but it can be used by IDES, linters, etc to help the programmer see type annotations.
Basically, it helps you - the programmer - see what type a object is. This will help you reduce bugs and help you manage a large code base.
QUESTION
I have been checking out this detr repository and the total number of classes are 100, but 10 of these are empty string as shown here.
Is there any particular reason behind this?
ANSWER
Answered 2020-Dec-17 at 13:18Basically, the COCO dataset was described in a paper before its release (you can find it here). At this point, the authors gave a list of the 91 types of objects that would be in the dataset.
But when the 2014 and 2017 datasets sere released, it turned out that you could find only 80 of these objects in the annotations.
The list you have is the original list of objects (as described in the paper) but with every object that does not appear in the 2014 and 2017 replaced by the empty string "".
My guess is that the sole purpose of keeping these "phantom" objects is to keep consistency with object ids that may have been fixed someday in the past.
If you want to learn more about it, you can look at this blog entry.
QUESTION
first time posting here ! If my question is lacking anything please tell me and I'll fix it !
Facebook recently released DETR, an object detection model using transformers ! The model is implemented with Pytorch and I'm trying to implement the loss function where Hungarian algorithm is involved but with Keras and Tensorflow as a custom loss function for Keras model. In the original implementation from Facebook, it's line 81-82 in https://github.com/facebookresearch/detr/blob/master/models/matcher.py
In order to use numpy and classic python function, I used:
...ANSWER
Answered 2020-Jul-01 at 09:32Does this work for you? See: https://www.tensorflow.org/api_docs/python/tf/numpy_function
QUESTION
I want to display images in a div according to select option (onclick = "DispImg()) I get 2 problem's
I store the images in array and I display all of theme and when you select an option it will automatically display the images that have the correct id .
and this is my script : I want to add to every image an id but the (setAttribute) method dosn't work and when you chose what id the script will display only the images that have the same id .
...ANSWER
Answered 2020-Feb-19 at 14:45Instead of setAttribute you can replace with just .id but both should work fine
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install detr
You can use detr like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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