xiaoxue_admin
/
supervision
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add mAP example to `README.md`

This commit is contained in:
Piotr Skalski 2023-08-07 12:03:38 +02:00 committed by GitHub
parent a6c73f70ec
commit 2c31f8ec94
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 32 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

40
README.md
View File

@ -31,7 +31,7 @@ Pip install the supervision package in a
pip install supervision[desktop]
```
Read more about desktop, headless and local installation in our [guide](https://roboflow.github.io/supervision/).
Read more about desktop, headless, and local installation in our [guide](https://roboflow.github.io/supervision/).
## 🔥 quickstart
@ -52,7 +52,7 @@ Read more about desktop, headless and local installation in our [guide](https://
<details close>
<summary>👉 more detections utils</summary>
- Easily switch inference pipeline between supported object detection / instance segmentation models
- Easily switch inference pipeline between supported object detection/instance segmentation models
```python
>>> import supervision as sv
@ -107,7 +107,7 @@ Read more about desktop, headless and local installation in our [guide](https://
<details close>
<summary>👉 more dataset utils</summary>
- Load object detection / instance segmentation datasets in one of supported formats
- Load object detection/instance segmentation datasets in one of the supported formats
```python
>>> dataset = sv.DetectionDataset.from_yolo(
@ -138,7 +138,7 @@ Read more about desktop, headless and local installation in our [guide](https://
[ 20.154999, 347.825 , 416.125 , 915.895 ]], dtype=float32)
```
- Split dataset for training, testing and validation
- Split dataset for training, testing, and validation
```python
>>> train_dataset, test_dataset = dataset.split(split_ratio=0.7)
@ -148,7 +148,7 @@ Read more about desktop, headless and local installation in our [guide](https://
(700, 150, 150)
```
- Merge multiple datasets together
- Merge multiple datasets
```python
>>> ds_1 = sv.DetectionDataset(...)
@ -170,7 +170,7 @@ Read more about desktop, headless and local installation in our [guide](https://
['cat', 'dog', 'person']
```
- Save object detection / instance segmentation datasets in one of supported formats
- Save object detection/instance segmentation datasets in one of the supported formats
```python
>>> dataset.as_yolo(
@ -203,7 +203,7 @@ Read more about desktop, headless and local installation in our [guide](https://
... )
```
- Load classification datasets in one of supported formats
- Load classification datasets in one of the supported formats
```python
>>> cs = sv.ClassificationDataset.from_folder_structure(
@ -211,7 +211,7 @@ Read more about desktop, headless and local installation in our [guide](https://
... )
```
- Save classification datasets in one of supported formats
- Save classification datasets in one of the supported formats
```python
>>> cs.as_folder_structure(
@ -245,6 +245,30 @@ array([
])
```
<details close>
<summary>👉 more metrics</summary>
- Mean average precision (mAP) for object detection tasks.
```python
>>> import supervision as sv
>>> dataset = sv.DetectionDataset.from_yolo(...)
>>> def callback(image: np.ndarray) -> sv.Detections:
... ...
>>> mean_average_precision = sv.MeanAveragePrecision.benchmark(
... dataset = dataset,
... callback = callback
... )
>>> mean_average_precision.map50_95
0.433
```
</details>
## 🎬 tutorials
<p align="left">