ann = prompt_process.point_prompt(points=[[200, 200]], pointlabel=[1])
prompt_process.plot(annotations=ann, output='./')
```
This snippet demonstrates the simplicity of loading a pre-trained model and running a prediction on an image.
This snippet demonstrates the simplicity of loading a pre-trained model and running a prediction on an image.
@ -83,15 +86,19 @@ This snippet demonstrates the simplicity of loading a pre-trained model and runn
Validation of the model on a dataset can be done as follows:
Validation of the model on a dataset can be done as follows:
```python
!!! example ""
from ultralytics import FastSAM
=== "Python"
```python
from ultralytics import FastSAM
# Create a FastSAM model
# Create a FastSAM model
model = FastSAM('FastSAM-s.pt') # or FastSAM-x.pt
model = FastSAM('FastSAM-s.pt') # or FastSAM-x.pt
# Validate the model
# Validate the model
results = model.val(data='coco8-seg.yaml')
results = model.val(data='coco8-seg.yaml')
```
```
Please note that FastSAM only supports detection and segmentation of a single class of object. This means it will recognize and segment all objects as the same class. Therefore, when preparing the dataset, you need to convert all object category IDs to 0.
Please note that FastSAM only supports detection and segmentation of a single class of object. This means it will recognize and segment all objects as the same class. Therefore, when preparing the dataset, you need to convert all object category IDs to 0.
@ -26,7 +26,7 @@ You can use many of these models directly in the Command Line Interface (CLI) or
## Usage
## Usage
This example provides simple inference code for YOLO, SAM and RTDETR models. For more options including handling inference results see [Predict](../modes/predict.md) mode. For using models with additional modes see [Train](../modes/train.md), [Val](../modes/val.md) and [Export](../modes/export.md).
This example provides simple inference code for YOLO, SAM and RTDETR models. For more options including handling inference results see [Predict](../modes/predict.md) mode. For using models with additional modes see [Train](../modes/train.md), [Val](../modes/val.md) and [Export](../modes/export.md).
@ -121,6 +124,7 @@ Below is an example of how to resume an interrupted training using Python and vi
# Resume training
# Resume training
results = model.train(resume=True)
results = model.train(resume=True)
```
```
=== "CLI"
=== "CLI"
```bash
```bash
@ -196,12 +200,15 @@ To use a logger, select it from the dropdown menu in the code snippet above and
To use Comet:
To use Comet:
```python
!!! example ""
# pip install comet_ml
import comet_ml
comet_ml.init()
=== "Python"
```
```python
# pip install comet_ml
import comet_ml
comet_ml.init()
```
Remember to sign in to your Comet account on their website and get your API key. You will need to add this to your environment variables or your script to log your experiments.
Remember to sign in to your Comet account on their website and get your API key. You will need to add this to your environment variables or your script to log your experiments.
@ -211,12 +218,15 @@ Remember to sign in to your Comet account on their website and get your API key.
To use ClearML:
To use ClearML:
```python
!!! example ""
# pip install clearml
import clearml
clearml.browser_login()
=== "Python"
```
```python
# pip install clearml
import clearml
clearml.browser_login()
```
After running this script, you will need to sign in to your ClearML account on the browser and authenticate your session.
After running this script, you will need to sign in to your ClearML account on the browser and authenticate your session.
@ -226,16 +236,22 @@ After running this script, you will need to sign in to your ClearML account on t
To use TensorBoard in [Google Colab](https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb):
To use TensorBoard in [Google Colab](https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb):
```bash
!!! example ""
load_ext tensorboard
tensorboard --logdir ultralytics/runs # replace with 'runs' directory
=== "CLI"
```
```bash
load_ext tensorboard
tensorboard --logdir ultralytics/runs # replace with 'runs' directory
```
To use TensorBoard locally run the below command and view results at http://localhost:6006/.
To use TensorBoard locally run the below command and view results at http://localhost:6006/.
```bash
!!! example ""
tensorboard --logdir ultralytics/runs # replace with 'runs' directory
```
=== "CLI"
```bash
tensorboard --logdir ultralytics/runs # replace with 'runs' directory
```
This will load TensorBoard and direct it to the directory where your training logs are saved.
This will load TensorBoard and direct it to the directory where your training logs are saved.
Full source code for this file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/amg.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/amg.py). Help us fix any issues you see by submitting a [Pull Request](https://docs.ultralytics.com/help/contributing/) 🛠️. Thank you 🙏!
Full source code for this file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/amg.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/models/sam/amg.py). Help us fix any issues you see by submitting a [Pull Request](https://docs.ultralytics.com/help/contributing/) 🛠️. Thank you 🙏!
Glenn Jocher
1 year ago
committed by
GitHub