Comments (3)
Thank you for your interest! We host models (MCNN + object detection)via provided pretrain links, which have been provided via google drives. Please follow the step in my description to inference your image.
Thank you and let me know if you have any further questions.
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Thank you for your interest! We host models (MCNN + object detection)via provided pretrain links, which have been provided via google drives. Please follow the step in my description to inference your image.
Thank you and let me know if you have any further questions.
thank you @Cli98
how I can use this architecture as end-to-end network?
I mean that: I want to get output of MCNN (for generating density maps) then crop regions and then fed this patchs to detector. but I don't know how?
imagine I want to reimplement it and train on visdrone dataset again.
appreciate if help.
thank you
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Hi @mahilaMoghadami
Thank you for your interest! We host models (MCNN + object detection)via provided pretrain links, which have been provided via google drives. Please follow the step in my description to inference your image.
Thank you and let me know if you have any further questions.thank you @Cli98 how I can use this architecture as end-to-end network? I mean that: I want to get output of MCNN (for generating density maps) then crop regions and then fed this patchs to detector. but I don't know how?
imagine I want to reimplement it and train on visdrone dataset again. appreciate if help. thank you
Following the steps here to make it end-to-end, in case you wanna to reimplement it.
- Run MCNN to get density crops. You can find it at here: https://github.com/CommissarMa/MCNN-pytorch, and pretrain weights here here
- Run code in image-cropping folder to generate image crops.
- for the crops+original image, use a state-of-the-art detector to detect , then run code in "fusion detection" to get final detection result.
In step #2, you can run this command to generate density crops:
python density_slide_window_official.py . HEIGHT_WIDTH THRESHOLD --output_folder Output_FolderName --mode val
Please replace all constant (in upper letter) with yours.
Let me know if you need any more help.
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Related Issues (20)
- Some problems HOT 2
- VisDrones object detection dataset how to generate density map and next step crop ? HOT 7
- About MCNN pretrained weights HOT 2
- how can i get the gaussian_kernels.pkl and distances_dict.pkl?
- can you share the code about uavdt format to json or xml format transform code? HOT 2
- Abount height and width of the sliding window HOT 2
- For object detection module, could you provide the config file for faster_rccn? HOT 2
- About the estimated density map HOT 7
- how to test any images?
- crop images HOT 10
- help HOT 1
- Not understanding density map generation using MCNN HOT 1
- crop HOT 1
- How to get the gt of visdrone dataset in MCNN HOT 1
- About train this model
- 数据集格式
- DMNet
- UAVDT dataset split
- 密度图生成
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