anylabeling installation and usage instructions

1.anylabeling instructions

Official website : https://anylabeling.nrl.ai/docs
As a smart labeling tool with Segment Anything and YOLO models, this tool can quickly and accurately label images.

2. Installation tutorial

1. Executable program mode

0. Download the executable program from the official website (https://github.com/vietanhdev/anylabeling/releases)
   

1. Check the required CUDA and cuDNN versions through the onnx official website (anylabeling version 0.3.3 uses onnxruntime-gpu 1.14, which needs to be adapted to CUDA 11.6 and cuDNN 8.5)
   

2. Install the corresponding versions of cuda and cuDNN as required.
   CUDA download address : https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64
   cuDNN download address : https://developer.nvidia.com/rdp/cudnn-archive

3. Run program
   

4. Change software language
   

5. Select automatic labeling, select from the model, and the software will automatically download the model (clicking to crash means that the download source cannot be connected and a VPN needs to be turned on). You
   
   
   can also choose to download the model directly from the official website (https://github.com/vietanhdev/anylabeling-assets/releases ) Download the corresponding version of the model and then load it directly (you know the download speed of github)
   

6. You can also go directly to see where the software itself was downloaded from. After running the software, you can see the folder where the model is saved under the path C:\Users***\anylabeling_data\models (the * represents the username of your computer). As shown in the figure below,
   
   the config.yaml in each folder saves the download path of the model. You can see it by opening it with txt:
   
   We open the path: https://huggingface.co/vietanhdev/segment-anything- onnx-models, you can enter the following web page:
   
   you can download the model file from here
   

7. Manually configure the model file.
   We unzip the downloaded file, open the config.yaml in it, and compare it with the original:

   config_file: C:\Users\aodeluo\anylabeling_data\models\mobile_sam_20230629\config.yaml
   display_name: Segment Anything (MobileSAM)
   download_url: https://huggingface.co/vietanhdev/segment-anything-onnx-models/resolve/main/mobile_sam_20230629.zip
   has_downloaded: false
   is_custom_model: false
   name: mobile_sam_20230629
   

   type: segment_anything
   name: mobile_sam_20230629
   display_name: Segment Anything (MobileSAM)
   encoder_model_path: mobile_sam.encoder.onnx
   decoder_model_path: sam_vit_h_4b8939.decoder.onnx
   input_size: 1024
   max_width: 1024
   max_height: 682
   

   We make the following modifications:
   

   type: segment_anything
   name: mobile_sam_20230629
   display_name: Segment Anything (MobileSAM)
   encoder_model_path: mobile_sam.encoder.onnx
   decoder_model_path: sam_vit_h_4b8939.decoder.onnx
   input_size: 1024
   max_width: 1024
   max_height: 682
   config_file: C:\Users\aodeluo\anylabeling_data\models\mobile_sam_20230629\config.yaml
   has_downloaded: true
   

   Then copy the entire file directly to the corresponding model directory for overwriting.
   
   Open anylabeling and select the replaced model.
   

   
   Open an image and you can automatically label it
   

2. python program

1. installation environment, environment

   conda create -n anylabeling python=3.8 anaconda
   conda activate anylabeling
   

2. Install anylabeling

   pip install anylabeling-gpu -i https://mirrors.aliyun.com/pypi/simple/
   

   

3. By pip listchecking the installed onnx version
   

4. Check the required CUDA and cuDNN versions through the onnx official website
   

5. Install the corresponding versions of cuda and cuDNN as required.
   CUDA download address : https://developer.nvidia.com/cuda-downloads?target_os=Windows&target_arch=x86_64
   cuDNN download address : https://developer.nvidia.com/rdp/cudnn-archive