update readme for ms2.3.1

mindspore-lab · Nov 6, 2024 · 687d0ae · 687d0ae
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diff --git a/GETTING_STARTED.md b/GETTING_STARTED.md
@@ -29,7 +29,7 @@ to understand their behavior. Some common arguments are:
 * Prepare your dataset in YOLO format. If trained with COCO (YOLO format), prepare it from [yolov5](https://github.com/ultralytics/yolov5) or the darknet.
 
   <details onclose>
-
+  <summary><b>View More</b></summary>
   ```
     coco/
       {train,val}2017.txt

diff --git a/README.md b/README.md
@@ -18,7 +18,7 @@ The following is the corresponding `mindyolo` versions and supported `mindspore`
 |  mindyolo  |  mindspore  |
 |    :--:    |     :--:    |
 |   master   |    master   |
-|    0.4     |    2.3.0    |
+|    0.4     |    2.3.1/2.3.0    |
 |    0.3     |    2.2.10   |
 |    0.2     |    2.0      |
 |    0.1     |    1.8      |

diff --git a/configs/yolov3/README.md b/configs/yolov3/README.md
@@ -14,17 +14,17 @@ We present some updates to YOLO! We made a bunch of little design changes to mak
 <details open markdown>
 <summary><b>performance tested on Ascend 910(8p) with graph mode</b></summary>
 
-| Name   |        Scale       | BatchSize | ImageSize | Dataset      | Box mAP (%) | Params |                Recipe                        | Download                                                                                                             |
-|--------|        :---:       |   :---:   |   :---:   |--------------|    :---:    |  :---: |                :---:                         |        :---:       |
-| YOLOv3 | Darknet53          |  16 * 8   |    640    | MS COCO 2017 |    45.5     | 61.9M  | [yaml](./yolov3.yaml)         | [weights](https://download.mindspore.cn/toolkits/mindyolo/yolov3/yolov3-darknet53_300e_mAP455-adfb27af.ckpt)         |
+| Model Name | Cards  | Batch Size | ImageSize |  jit_level  | graph compile | Box mAP (%) | Params |                Recipe                        | Download                                                                                                             |
+|:------:|    :---:   |   :---:    |   :---:   |    :---:    |     :---:     |    :---:    |  :---: |                :---:                         |        :---:       |
+| YOLOv3 |      8     |    16      |    640    |     O2      |    5 mins     |   45.5      | 61.9M  | [yaml](./yolov3.yaml)         | [weights](https://download.mindspore.cn/toolkits/mindyolo/yolov3/yolov3-darknet53_300e_mAP455-adfb27af.ckpt)         |
 </details>
 
 <details open markdown>
 <summary><b>performance tested on Ascend 910*(8p)</b></summary>
 
-| Name   |        Scale       | BatchSize | ImageSize | Dataset      | Box mAP (%) | ms/step | Params |                Recipe                        | Download                                                                                                             |
-|--------|        :---:       |   :---:   |   :---:   |--------------|    :---:    |  :---:  |  :---: |                :---:                         |        :---:       |
-| YOLOv3 | Darknet53          |  16 * 8   |    640    | MS COCO 2017 |     46.6    | 396.60  | 61.9M  | [yaml](./yolov3.yaml)         | [weights](https://download-mindspore.osinfra.cn/toolkits/mindyolo/yolov3/yolov3-darknet53_300e_mAP455-81895f09-910v2.ckpt)         |
+| Model Name | Cards  | Batch Size | ImageSize |  jit_level  | graph compile | Box mAP (%) | ms/step | Params |                Recipe                        | Download                                                                                                             |
+|:------:|    :---:   |   :---:    |   :---:   |    :---:    |     :---:     |   :---:    |  :---:  |  :---: |                :---:                         |        :---:       |
+| YOLOv3 |      8     |    16      |    640    |     O2      |    5 mins     |   46.6    | 396.60  | 61.9M  | [yaml](./yolov3.yaml)         | [weights](https://download-mindspore.osinfra.cn/toolkits/mindyolo/yolov3/yolov3-darknet53_300e_mAP455-81895f09-910v2.ckpt)         |
 </details>
 
 <br>
@@ -38,9 +38,16 @@ We present some updates to YOLO! We made a bunch of little design changes to mak
 
 Please refer to the [GETTING_STARTED](https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md) in MindYOLO for details.
 
+### Requirements
+
+| mindspore | ascend driver | firmware     | cann toolkit/kernel
+| :-------: | :-----------: | :----------: | :----------------:
+| 2.3.1     | 24.1.RC2      | 7.3.0.1.231  | 8.0.RC2.beta1
+
 ### Training
 
-<details open>
+<details open markdown>
+<summary><b>View More</b></summary>
 
 #### - Pretraining Model
 

diff --git a/configs/yolov4/README.md b/configs/yolov4/README.md
@@ -52,9 +52,16 @@ AP (65.7% AP50) for the MS COCO dataset at a realtime speed of 65 FPS on Tesla V
 
 Please refer to the [GETTING_STARTED](https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md) in MindYOLO for details.
 
+### Requirements
+
+| mindspore | ascend driver | firmware     | cann toolkit/kernel
+| :-------: | :-----------: | :----------: | :----------------:
+| 2.3.1     | 24.1.RC2      | 7.3.0.1.231  | 8.0.RC2.beta1
+
 ### Training
 
 <details open>
+<summary><b>View More</b></summary>
 
 #### - Pretraining Model
 

diff --git a/configs/yolov5/README.md b/configs/yolov5/README.md
@@ -41,9 +41,16 @@ YOLOv5 is a family of object detection architectures and models pretrained on th
 
 Please refer to the [GETTING_STARTED](https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md) in MindYOLO for details.
 
+### Requirements
+
+| mindspore | ascend driver | firmware     | cann toolkit/kernel
+| :-------: | :-----------: | :----------: | :----------------:
+| 2.3.1     | 24.1.RC2      | 7.3.0.1.231  | 8.0.RC2.beta1
+
 ### Training
 
 <details open>
+<summary><b>View More</b></summary>
 
 #### - Distributed Training
 

diff --git a/configs/yolov7/README.md b/configs/yolov7/README.md
@@ -42,9 +42,16 @@ YOLOv7 surpasses all known object detectors in both speed and accuracy in the ra
 
 Please refer to the [GETTING_STARTED](https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md) in MindYOLO for details.
 
+### Requirements
+
+| mindspore | ascend driver | firmware     | cann toolkit/kernel
+| :-------: | :-----------: | :----------: | :----------------:
+| 2.3.1     | 24.1.RC2      | 7.3.0.1.231  | 8.0.RC2.beta1
+
 ### Training
 
 <details open>
+<summary><b>View More</b></summary>
 
 #### - Distributed Training
 

diff --git a/configs/yolov8/README.md b/configs/yolov8/README.md
@@ -51,9 +51,16 @@ Ultralytics YOLOv8, developed by Ultralytics, is a cutting-edge, state-of-the-ar
 
 Please refer to the [GETTING_STARTED](https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md) in MindYOLO for details.
 
+### Requirements
+
+| mindspore | ascend driver | firmware     | cann toolkit/kernel
+| :-------: | :-----------: | :----------: | :----------------:
+| 2.3.1     | 24.1.RC2      | 7.3.0.1.231  | 8.0.RC2.beta1
+
 ### Training
 
 <details open>
+<summary><b>View More</b></summary>
 
 #### - Distributed Training
 

diff --git a/configs/yolox/README.md b/configs/yolox/README.md
@@ -41,9 +41,16 @@ YOLOX is a new high-performance detector with some experienced improvements to Y
 
 Please refer to the [GETTING_STARTED](https://github.com/mindspore-lab/mindyolo/blob/master/GETTING_STARTED.md) in MindYOLO for details.
 
+### Requirements
+
+| mindspore | ascend driver | firmware     | cann toolkit/kernel
+| :-------: | :-----------: | :----------: | :----------------:
+| 2.3.1     | 24.1.RC2      | 7.3.0.1.231  | 8.0.RC2.beta1
+
 ### Training
 
 <details open>
+<summary><b>View More</b></summary>
 
 #### - Distributed Training
 

diff --git a/docs/en/index.md b/docs/en/index.md
@@ -25,7 +25,7 @@ The following is the corresponding `mindyolo` versions and supported `mindspore`
 |  mindyolo  |  mindspore  |
 |    :--:    |     :--:    |
 |   master   |    master   |
-|    0.4     |    2.3.0    |
+|    0.4     |    2.3.1/2.3.0    |
 |    0.3     |    2.2.10   |
 |    0.2     |    2.0      |
 |    0.1     |    1.8      |

diff --git a/docs/zh/index.md b/docs/zh/index.md
@@ -24,7 +24,7 @@ MindYOLO基于mindspore实现了最新的YOLO系列算法。以下是mindyolo的
 |  mindyolo  |  mindspore  |
 |    :--:    |     :--:    |
 |   master   |    master   |
-|    0.4     |    2.3.0    |
+|    0.4     |    2.3.1/2.3.0    |
 |    0.3     |    2.2.10   |
 |    0.2     |    2.0      |
 |    0.1     |    1.8      |