clip

Table of contents

• clip
  • Table of contents
  • 1. Description
  • 2. Current Support Platform
  • 3. Pretrained Model
  • 4. Convert to RKNN
  • 5. Python Demo
  • 6. Android Demo
    • 6.1 Compile and Build
    • 6.2 Push demo files to device
    • 6.3 Run demo
  • 7. Linux Demo
    • 7.1 Compile and Build
    • 7.2 Push demo files to device
    • 7.3 Run demo
  • 8. Expected Results

1. Description

The model used in this example comes from the following open source projects: https://huggingface.co/openai/clip-vit-base-patch32

2. Current Support Platform

RK3562, RK3566, RK3568, RK3576, RK3588, RV1126B

3. Pretrained Model

Download link:

./clip_images.onnx
./clip_text.onnx

Download with shell command:

cd model
./download_model.sh

4. Convert to RKNN

Usage:

cd python
python convert.py <onnx_model> <TARGET_PLATFORM> <output_rknn_path(optional)>

# such as: 
python convert.py ../model/clip_images.onnx rk3588
# output model will be saved as ../model/clip_images.rknn

Description:

• <onnx_model>: Specify ONNX model path.
• <TARGET_PLATFORM>: Specify NPU platform name. Support Platform refer here.
• <output_rknn_path>(optional): Specify save path for the RKNN model, default save in the same directory as ONNX model with name clip_images.rknn

Note:

For export clip onnx model, please refer to export_onnx.md

5. Python Demo

Usage:

cd python

# Inference with RKNN model
python clip.py --text_model <rknn_model> --img_model <rknn_model> --target <TARGET_PLATFORM>

Description:

• <TARGET_PLATFORM>: Specify NPU platform name. Such as 'rk3576'.
• <rknn_model>: specified as the model path.

6. Android Demo

6.1 Compile and Build

Usage:

# go back to the rknn_model_zoo root directory
cd ../../
export ANDROID_NDK_PATH=<android_ndk_path>

./build-android.sh -t <TARGET_PLATFORM> -a <ARCH> -d clip

# such as 
./build-android.sh -t rk3588 -a arm64-v8a -d clip

Description:

• <android_ndk_path>: Specify Android NDK path.
• <TARGET_PLATFORM>: Specify NPU platform name. Support Platform refer here.
• <ARCH>: Specify device system architecture. To query device architecture, refer to the following command:

  # Query architecture. For Android, ['arm64-v8a' or 'armeabi-v7a'] should shown in log.
  adb shell cat /proc/version
  

6.2 Push demo files to device

With device connected via USB port, push demo files to devices:

adb root
adb remount
adb push install/<TARGET_PLATFORM>_android_<ARCH>/rknn_clip_demo/ /data/

6.3 Run demo

adb shell
cd /data/rknn_clip_demo

export LD_LIBRARY_PATH=./lib
./rknn_clip_demo clip_images_fp16.rknn model/dog_224x224.jpg clip_text_fp16.rknn model/text.txt

7. Linux Demo

7.1 Compile and Build

usage

# go back to the rknn_model_zoo root directory
cd ../../

# if GCC_COMPILER not found while building, please set GCC_COMPILER path
(optional)export GCC_COMPILER=<GCC_COMPILER_PATH>

./build-linux.sh -t <TARGET_PLATFORM> -a <ARCH> -d clip

# such as 
./build-linux.sh -t rk3588 -a aarch64 -d clip

Description:

• <GCC_COMPILER_PATH>: Specified as GCC_COMPILER path.

• <TARGET_PLATFORM> : Specify NPU platform name. Support Platform refer here.

• <ARCH>: Specify device system architecture. To query device architecture, refer to the following command:

  # Query architecture. For Linux, ['aarch64' or 'armhf'] should shown in log.
  adb shell cat /proc/version
  

7.2 Push demo files to device

• If device connected via USB port, push demo files to devices:

adb push install/<TARGET_PLATFORM>_linux_<ARCH>/rknn_clip_demo/ /userdata/

• For other boards, use scp or other approaches to push all files under install/<TARGET_PLATFORM>_linux_<ARCH>/rknn_clip_demo/ to userdata.

7.3 Run demo

adb shell
cd /userdata/rknn_clip_demo

export LD_LIBRARY_PATH=./lib
./rknn_clip_demo clip_images_fp16.rknn model/dog_224x224.jpg clip_text_fp16.rknn model/text.txt

8. Expected Results

This example will print the labels and corresponding scores of the test image detect results, as follows:

      images                 text         score  
-------------------------------------------------
model/dog_224x224.jpg @ a photo of a dog: 0.989

• Note: Different platforms, different versions of tools and drivers may have slightly different results.