Automatic Object Detection with SAM Meta
In addition to traditional image segmentation approaches, IPSDK now integrates advanced automatic segmentation capabilities based on the SAM (Segment Anything Model) developed by Meta. The model delivers very high-quality results from the very first use, without any training phase or data preparation.
The Automatic Object Segmentation module automatically detects and segments objects present in an image, even in complex or heterogeneous scenes. Additional parameters allow users to refine the segmentation, filter detected objects, and precisely adapt the results to specific application needs.
Furthermore, the integration of SAM into IPSDK Explorer makes the results immediately usable thanks to integrated post-processing tools. It is also possible to generate scripts based on these models to automatically process large volumes of images.
To Sum up…
What is SAM Meta?
The Segment Anything Model (SAM) developed by Meta is an artificial intelligence model pre-trained on very large image datasets. It can automatically identify and segment objects present in an image without any specific training phase, producing precise and detailed masks.
Within IPSDK Explorer, these complex models can be used in just a few clicks. Integrated post-processing tools make the results immediately usable, with the option, if needed, to rely on a probability map to control and refine the segmentation.
⇒ Using SAM Meta in IPSDK Explorer:
- Segmentation results that are highly accurate from the very first use, with parameters available to refine them if needed.
- Model selection based on the desired trade-off between speed and accuracy.
- Simple filtering of detected objects: removal of objects that are too small or touching the border.
- Detection and removal of outliers to discard objects that deviate from the majority population.
- Ability to control the results using the probability map.