<jupyter_start><jupyter_text>View source on github        Run in Google Colab  Clone the github repository for the DETR and install other dependencies<jupyter_code>!git clone https://github.com/facebookresearch/detr.git
!pip install cython scipy
!pip install -U 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'<jupyter_output><empty_output><jupyter_text>Setting up the Directory(Either use the following code from the terminal in your wokrspace directory or make the directory in the way shown at the last first)<jupyter_code>!mkdir path
cd path
!mkdir to
cd to
!mkdir coco
cd coco<jupyter_output><empty_output><jupyter_text>Path formed will be in case of google colab : "/content/path/to/coco"For personal machine: "./path/to/coco"  Preparing the dataset<jupyter_code>!wget http://images.cocodataset.org/zips/train2017.zip
!wget http://images.cocodataset.org/zips/val2017.zip
!wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
!unzip /content/path/to/coco/train2017.zip
!unzip /content/path/to/coco/val2017.zip
!unzip /content/path/to/coco/annotation_trainval2017.zip<jupyter_output><empty_output><jupyter_text>You can delete the zipped files after unzipping them Make sure to change the directory back to the cloned repository before running the following command which will be "/content/detr" in case of google colab and "./detr" in case of your personal machine  Models provided by Facebook AI:1. https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth (FOR DETR-R50)2. https://dl.fbaipublicfiles.com/detr/detr-r50-dc5-f0fb7ef5.pth (FOR DETR-R50-DC5)3. https://dl.fbaipublicfiles.com/detr/detr-r101-2c7b67e5.pth (FOR DETR-R101)4. https://dl.fbaipublicfiles.com/detr/detr-r101-dc5-a2e86def.pth FOR DETR_R101-DC5) For changing the model choosen for evaluation we can  change the link below with four of the folowing mentioned above.<jupyter_code>!python main.py --batch_size 2 --no_aux_loss --eval --resume https://dl.fbaipublicfiles.com/detr/detr-r50-e632da11.pth --coco_path /content/path/to/coco<jupyter_output><empty_output><jupyter_text>Below is shown how the data should be kept for running the above code ![Screenshot from 2021-02-18 18-55-22.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAW8AAADACAYAAADLAeKbAAAABHNCSVQICAgIfAhkiAAAABl0RVh0U29mdHdhcmUAZ<KEY>2NyZW<KEY>jPUARmPWrFlkZmZiMBgG3b9z505yc3Ov8qgujyb2KfJX6inP/hVb7GM9GiGEWqhq5p2VlTVkcAMkJiaSlZV1FUc0SsbHWL/hRRaFjvVAhBBqp6qZ90033TRsm8TERBITEy/axm63s3btWg4dOuSroQkhxFWlqvD2FYPBQGZ<KEY>)<jupyter_code><jupyter_output><empty_output>
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{'chain_length': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '526552', 'license': 'Apache-2.0', 'n_tokens_mistral': 1076, 'n_tokens_neox': 986, 'n_words': 196, 'path': 'Evaluation_DETR.ipynb', 'repo_name': 'Dhruv0208/detr', 'size': '16739'}