docs: update readme

Dockerfile

@@ -1,12 +1,13 @@
 FROM git.modelhub.org.cn:9443/enginex-metax/maca-c500-pytorch:2.33.0.6-torch2.6-py310-ubuntu24.04-amd64
 
 RUN /opt/conda/bin/pip install funasr modelscope huggingface_hub
+RUN /opt/conda/bin/pip install openai-whisper
 
-RUN chmod 1777 -R /tmp && apt update && apt install -y ffmpeg
+# RUN chmod 1777 -R /tmp && apt update && apt install -y ffmpeg
 
 WORKDIR /opt/app
 COPY ./ ./
 RUN /opt/conda/bin/pip install -r requirements.txt
 
 EXPOSE 80
-ENTRYPOINT ["python3", "./test_funasr.py"]
+ENTRYPOINT ["/opt/conda/bin/python3", "./test_funasr.py"]

README.md

@@ -1,7 +1,7 @@
 # 沐曦 MetaX C500 FunASR
 
 ## 镜像构造
-```shell
+```bash
 docker build -t <built_img> .
 ```
 
@@ -9,19 +9,19 @@ docker build -t <built_img> .
 ### 快速镜像测试
 对funasr的测试需要在以上构造好的镜像容器内测试，测试步骤
 1. 本项目中附带上了示例测试数据，音频文件为`lei-jun-test.wav`，音频的识别准确内容文件为`lei-jun.txt`，用户需要准备好相应的ASR模型路径，本例中假设我们已经下载好了SenseVoiceSmall模型存放于/model/SenseVoiceSmall
-2. 在本项目路径下执行以下快速测试命令
-```shell
-metax-docker run -it \ 
-    --gpus=[0] \
-    -v $PWD:/tmp/workspace \
-    -v /model:/model \
-    -e MODEL_DIR=/model/SenseVoiceSmall \
-    -e TEST_FILE=lei-jun-test.wav \
-    -e ANSWER_FILE=lei-jun.txt \
-    -e RESULT_FILE=result.json \
-    --cpus=4 --memory=16g \
-    <built_img>
-```
+2. 在本项目路径下执行以下快速测试命令, 如果安装了 [metax-docker](https://developer.metax-tech.com/softnova/category?package_kind=Cloud&dimension=metax&chip_name=%E6%9B%A6%E4%BA%91C500%E7%B3%BB%E5%88%97&deliver_type=%E5%88%86%E5%B1%82%E5%8C%85&series_name=metax-docker):
+    ```bash
+    metax-docker run -it \ 
+        --gpus=[0] \
+        -v $PWD:/tmp/workspace \
+        -v /model:/model \
+        -e MODEL_DIR=/model/SenseVoiceSmall \
+        -e TEST_FILE=lei-jun-test.wav \
+        -e ANSWER_FILE=lei-jun.txt \
+        -e RESULT_FILE=result.json \
+        --cpus=4 --memory=16g \
+        <built_img>
+    ```
 上述测试指令成功运行将会在terminal中看到对测试音频的识别结果，运行时间以及1-cer效果指标，并且当前文件下会生成一个`result.json`文件记录刚才的测试结果
 
 ### 定制化手动运行
@@ -37,4 +37,4 @@ metax-docker run -it \
 | whisper | https://www.modelscope.cn/models/iic/Whisper-large-v3 | 23.8337 | ? | 0.910150 | ? |  |
 | paraformer | https://modelscope.cn/models/iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch | 3.9888 | 4.8517 | 0.955075 | 0.955075 |  |
 | conformer | https://www.modelscope.cn/models/iic/speech_conformer_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch | 80.4228 | 78.2914 | 0.349418 | 0.346090 |  |
-| uni_asr | https://www.modelscope.cn/models/iic/speech_UniASR-large_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline | 90.8399 | 68.6999 | 0.717138 | 0.717138 | 该部分的适配修改了一些funASR源码 |
+| uni_asr | https://www.modelscope.cn/models/iic/speech_UniASR-large_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline | 90.8399 | 68.6999 | 0.717138 | 0.717138 | |