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@ -113,8 +113,8 @@ YOLOv8 can process different types of input sources for inference, as shown in t |
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| OpenCV | `cv2.imread('im.jpg')` | `np.ndarray` | HWC format with BGR channels `uint8 (0-255)`. | |
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| numpy | `np.zeros((640,1280,3))` | `np.ndarray` | HWC format with BGR channels `uint8 (0-255)`. | |
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| torch | `torch.zeros(16,3,320,640)` | `torch.Tensor` | BCHW format with RGB channels `float32 (0.0-1.0)`. | |
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| CSV | `'sources.csv'` | `str` or `Path` | CSV file containing paths to images, videos, or directories. |
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| TXT | `'sources.txt'` | `str` or `Path` | TXT file containing paths to images, videos, or directories. | |
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| CSV | `'sources.csv'` | `str` or `Path` | CSV file containing paths to images, videos, or directories. | |
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| TXT | `'sources.txt'` | `str` or `Path` | TXT file containing paths to images, videos, or directories. | |
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| video ✅ | `'video.mp4'` | `str` or `Path` | Video file in formats like MP4, AVI, etc. | |
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| directory ✅ | `'path/'` | `str` or `Path` | Path to a directory containing images or videos. | |
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| glob ✅ | `'path/*.jpg'` | `str` | Glob pattern to match multiple files. Use the `*` character as a wildcard. | |
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@ -260,8 +260,7 @@ Below are code examples for using each source type: |
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# Run inference on the source |
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results = model(source) # list of Results objects |
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=== "TXT" |
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"TXT" |
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Run inference on a collection of images, videos and directories listed in a TXT file. |
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```python |
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