Update Python example

pull/13543/head
Glenn Jocher 2025-03-23 12:05:25 +01:00
parent 353b892c45
commit 480a53c640
2 changed files with 16 additions and 16 deletions

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@ -77,7 +77,7 @@ pip install -r requirements.txt # install
</details>
<details>
<details open>
<summary>Inference</summary>
YOLOv5 [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading/) inference. [Models](https://github.com/ultralytics/yolov5/tree/master/models) download automatically from the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
@ -85,17 +85,17 @@ YOLOv5 [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_m
```python
import torch
# Model
model = torch.hub.load("ultralytics/yolov5", "yolov5s") # or yolov5n - yolov5x6, custom
# Load YOLOv5 model (options: yolov5n, yolov5s, yolov5m, yolov5l, yolov5x)
model = torch.hub.load("ultralytics/yolov5", "yolov5s")
# Images
img = "https://ultralytics.com/images/zidane.jpg" # or file, Path, PIL, OpenCV, numpy, list
# Input source (URL, file, PIL, OpenCV, numpy array, or list)
img = "https://ultralytics.com/images/zidane.jpg"
# Inference
# Perform inference (handles batching, resizing, normalization)
results = model(img)
# Results
results.print() # or .show(), .save(), .crop(), .pandas(), etc.
# Process results (options: .print(), .show(), .save(), .crop(), .pandas())
results.print()
```
</details>

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@ -73,7 +73,7 @@ cd yolov5
pip install -r requirements.txt # install
```
</details>
</details open>
<details>
<summary>推理</summary>
@ -83,17 +83,17 @@ pip install -r requirements.txt # install
```python
import torch
# Model
model = torch.hub.load("ultralytics/yolov5", "yolov5s") # or yolov5n - yolov5x6, custom
# 加载 YOLOv5 模型 (选项: yolov5n, yolov5s, yolov5m, yolov5l, yolov5x)
model = torch.hub.load("ultralytics/yolov5", "yolov5s")
# Images
img = "https://ultralytics.com/images/zidane.jpg" # or file, Path, PIL, OpenCV, numpy, list
# 输入源 (URL, 文件, PIL, OpenCV, numpy 数组, 或列表)
img = "https://ultralytics.com/images/zidane.jpg"
# Inference
# 执行推理 (自动处理批处理, 调整大小, 标准化)
results = model(img)
# Results
results.print() # or .show(), .save(), .crop(), .pandas(), etc.
# 处理结果 (选项: .print(), .show(), .save(), .crop(), .pandas())
results.print()
```
</details>