Object detection Using Detection Transformer (Detr) on custom dataset

Step by step implementation of Object detection Using Detection Transformer (Detr) on custom dataset.

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DETR stands for "DEtection TRansformer," is a object detection model that uses a transformer architecture.
It was introduced in a research paper titled "End-to-End Object Detection with Transformers," published by researchers from Facebook AI Research (FAIR) in 2020.
CNN extracts features and then send them to transformer for relationship modeling and then obtained output is matches with the ground truth on the picture using bipartite graph matching algorithm.

The features extracted by CNN are flattened and then positional encoding is added to obtain the sequence features which are then fed to transformer encoder.
Each encoder layer contains self attention mechanism and each decoder contains self attention and cross-attention.

#transformers #detr #computervision

[KumDestiny]

Thanks for making me finally understand Detection transformers.

[wiemrebhi]

thank you for this video
i would like to ask you if i want to continue training the model from the last epoch what should i do

[KumDestiny]

Thanks again for the series your explanation made me to understand many things

[hieuquang-rj]

hi, in i cant run because AttributeError: type object 'Detections' has no attribute 'from_coco_annotations' in
detections =
how can u help me, thank you so much

[grayelearning]

While running the code, I am getting an error NameError: name 'CHECKPOINT' is not defined = Detr(lr=1e-4, lr_backbone=1e-5, weight_decay=1e-4) in this line . How to fix this issue?

[rickyS-D]

Great! very cool :) ... do you have any videos for detecting objects from videos using ViT pretained model or custom dataset.

[divyakrishnan]

Mam, is there any way to get the precision recall values for vision transformer after training?

[eranfeit]

Hi,

Great tutorial .
The training process take a lots of time . About 7 hours.
How to you estimate the number of Epochs ?

Eran

[hasancan]

In save and load part ı have a error. ıt said model.device is not defined. What can ı do for this error? Can u help me?

[mohammadyahya]

Thank you very much! Why we need it please if we have YOLOv8 for example?

[Sunil-ezhx]

Thank you soo much mam for this amazing video

[munkuo]

What is sv in box_annotator = sv.BoxAnnotator() ? A lot of place it's initialized but I could not find the reference to any module! Thanks in advance.

[lootere]

Does the summary function works for model containing transformer layers cause in my case its showing error

[alexandrebensi]

Thanks!! What is diference of this to yolo?

[xiaoyisongxiao]

hi i want Use DETR network to predict and calculate the missed detection rate and could you tell me how to finlish it? thanks!

[arnavthakur]

Very knowledgeable video, keep sharing mam all these valuable stuff

[KumDestiny]

When i was making more researches on the different types of vision transformers i saw the Vanilla vision transformers but i read the paper and didn't really understand. Can you help me for a tutorial on that please

[bilalsidiqi]

Hi, thank you for this tutorial, I have a question about segmentation and tracking. Is there a tracking algorithm with takes segmentation mask as input and shows segmentation instead of bounding box in the output? Thank you

[kaihennig]

Thank you very much for this tutorial. I tried to replicate it. But i got the error

"NameError: name 'image_processor' is not defined"

while trying to run the following line

"TRAIN_DATASET = CocoDetection(image_directory_path=TRAIN_DIRECTORY, image_processor=image_processor, train=True)".

Did anyone of you have the same problem? How did you fix it? As what do I need to initialize image_preprocessor beforehand?

[PunitKaushik-hu]

Hi arohi, I am getting this error while doing the training part, rest of the errors I have solved as there is lot of missing code in this but this one I was not able to solve :

NameError Traceback (most recent call last)
in <cell line: 1>()
----> 1 model = Detr(lr=1e-4, lr_backbone=1e-5, weight_decay=1e-4)
2
3 batch = next(iter(TRAIN_DATALOADER))
4 outputs = model(pixel_values=batch['pixel_values'],

in __init__(self, lr, lr_backbone, weight_decay)
9 super().__init__()
10 self.model =
---> 11 pretrained_model_name_or_path=CHECKPOINT,
12 num_labels=len(id2label),
13 ignore_mismatched_sizes=True

NameError: name 'CHECKPOINT' is not defined