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--- |
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language: |
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- en |
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library_name: ultralytics |
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pipeline_tag: image-classification |
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tags: |
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- action |
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--- |
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## How to Use |
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To use this model in your project, follow the steps below: |
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### 1. Installation |
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Ensure you have the `ultralytics` library installed, which is used for YOLO models: |
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```bash |
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pip install ultralytics |
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``` |
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```text |
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# class |
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calling |
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clapping |
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cycling |
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dancing |
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drinking |
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eating |
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fighting |
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hugging |
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laughing |
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listening_to_music |
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running |
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sitting |
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sleeping |
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texting |
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using_laptop |
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``` |
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### 2. Load the Model |
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You can load the model and perform detection on an image as follows: |
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```python |
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from ultralytics import YOLO |
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# Load the model |
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model = YOLO("./action-11x.pt") |
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# Perform detection on an image |
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results = model("image.png") |
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# Display or process the results |
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results.show() # This will display the image with detected objects |
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``` |
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### 3. Model Inference |
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The results object contains bounding boxes, labels (e.g., numbers or operators), and confidence scores for each detected object. |
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Access them like this: |
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```python |
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# View results |
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for r in results: |
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print(r.probs) # print the Probs object containing the detected class probabilities |
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``` |
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