From 67e07cb39cbd722b32dd180578fd49e4709c15e5 Mon Sep 17 00:00:00 2001
From: lrving <2415912278@qq.com>
Date: Wed, 19 Oct 2022 06:13:55 +0000
Subject: [PATCH] add ACL_TensorFlow/built-in/cv/YOLOv3_for_ACL/README_EN.md.

Signed-off-by: lrving <2415912278@qq.com>
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+English|[中文](README.md)
+
+# Yolov3 Inference for Tensorflow 
+
+This repository provides a script and recipe to Inference the Yolov3 model.
+
+## Notice
+**This sample only provides reference for you to learn the Ascend software stack and is not for commercial purposes.**
+
+Before starting, please pay attention to the following adaptation conditions. If they do not match, may leading in failure.
+
+| Conditions | Need |
+| --- | --- |
+| CANN Version | >=5.0.3 |
+| Chip Platform| Ascend310/Ascend310P3 |
+| 3rd Party Requirements| Please follow the 'requirements.txt' |
+
+## Quick Start Guide
+
+### 1. Clone the respository
+
+```shell
+git clone https://gitee.com/ascend/ModelZoo-TensorFlow.git
+cd Modelzoo-TensorFlow/ACL_TensorFlow/built-in/cv/YOLOv3_for_ACL
+```
+
+### 2. Requirements
+
+opencv-python==4.2.0.34
+
+
+### 3. Download and preprocess the dataset
+
+1. dataset
+  To compare with official implement, for example, we use [get_coco_dataset.sh](https://github.com/pjreddie/darknet/blob/master/scripts/get_coco_dataset.sh) to prepare our dataset.
+
+2. annotation file
+
+   cd scripts
+
+   Using script generate `coco2014_minival.txt` file. Modify the path in `coco_minival_anns.py` and `5k.txt`, then execute:
+
+   ```
+   python3 coco_minival_anns.py
+   ```
+
+   One line for one image, in the format like `image_index image_absolute_path img_width img_height box_1 box_2 ... box_n`.    
+   Box_x format: 
+
+   - `label_index x_min y_min x_max y_max`. (The origin of coordinates is at the left top corner, left top => (xmin, ymin), right bottom => (xmax, ymax).)    
+   - `image_index` is the line index which starts from zero. `label_index` is in range [0, class_num - 1].
+
+   For example:
+
+   ```
+   0 xxx/xxx/a.jpg 1920 1080 0 453 369 473 391 1 588 245 608 268
+   1 xxx/xxx/b.jpg 1920 1080 1 466 403 485 422 2 793 300 809 320
+   ...
+   ```
+
+
+### 3. Offline Inference
+
+**Convert pb to om.**
+
+- configure the env
+
+  Please follow the [guide](https://gitee.com/ascend/ModelZoo-TensorFlow/wikis/02.%E7%A6%BB%E7%BA%BF%E6%8E%A8%E7%90%86%E6%A1%88%E4%BE%8B/Ascend%E5%B9%B3%E5%8F%B0%E6%8E%A8%E7%90%86%E7%8E%AF%E5%A2%83%E5%8F%98%E9%87%8F%E8%AE%BE%E7%BD%AE?sort_id=6458719) to set the envs
+
+- convert pb to om
+
+  [pb download link](https://obs-9be7.obs.cn-east-2.myhuaweicloud.com/003_Atc_Models/modelzoo/yolov3_tf.pb)
+
+  For Ascend310:
+  ```
+  atc --model=yolov3_tf.pb --framework=3 --output=yolov3_tf_aipp --output_type=FP32 --soc_version=Ascend310 --input_shape="input:1,416,416,3" --log=info --insert_op_conf=yolov3_tf_aipp.cfg
+  ```
+  For Ascend310P3:
+  ```
+  atc --model=yolov3_tf.pb --framework=3 --output=yolov3_tf_aipp --output_type=FP32 --soc_version=Ascend310P3 --input_shape="input:1,416,416,3" --log=info --insert_op_conf=yolov3_tf_aipp.cfg
+  ```
+
+- Build the program
+
+  For Ascend310:
+  ```
+  unset ASCEND310P3_DVPP
+  bash build.sh
+  ```
+  For Ascend310P3:
+  ```
+  export ASCEND310P3_DVPP=1
+  bash build.sh
+  ```
+
+- Run the program:
+
+  ```
+  cd scripts
+  bash benchmark_tf.sh --batchSize=1 --modelType=yolov3 --imgType=raw --precision=fp16 --outputType=fp32 --useDvpp=1 --deviceId=0 --modelPath=yolov3_tf_aipp.om --trueValuePath=instance_val2014.json --imgInfoFile=coco2014_minival.txt --classNamePath=../../coco.names
+  ```
+
+
+
+## Performance
+
+### Result
+
+Our result were obtained by running the applicable inference script. To achieve the same results, follow the steps in the Quick Start Guide.
+
+#### Inference accuracy results
+
+IoU=0.5
+| model  | Npu_nums | **mAP** | 
+| :----: | :------: | :-----: | 
+| Yolov3 |    1     |  55.3%   | 
+
+## Reference
+[1] https://gitee.com/ascend/ModelZoo-TensorFlow/tree/master/TensorFlow/built-in/cv/detection/YoloV3_ID0076_for_TensorFlow
-- 
Gitee