| | --- |
| | language: en |
| | license: mit |
| | tags: |
| | - instance-segmentation |
| | - detectron2 |
| | - pytorch |
| | datasets: |
| | - custom-dataset |
| | metrics: |
| | - mean-average-precision |
| | pipeline_tag: object-detection |
| | labels: |
| | - background |
| | - germinated |
| | - non-germinated |
| | --- |
| | |
| |
|
| | # Instance Segmentation Model |
| |
|
| | ## Description |
| | This model performs instance segmentation using Mask R-CNN. It was trained on a custom dataset containing [X] images with [Y] classes. |
| |
|
| | ## Training Data |
| | - Dataset: [Germination Images] |
| | - Number of Images: [22] |
| | - Number of Classes: [2] |
| |
|
| | ## Usage |
| | Load the model using: |
| | ```python |
| | from transformers import AutoModelForObjectDetection, AutoFeatureExtractor |
| | |
| | model = AutoModelForObjectDetection.from_pretrained("Dreamy0/GermiNet-instance-segmentation") |
| | feature_extractor = AutoFeatureExtractor.from_pretrained("Dreamy0/GermiNet-instance-segmentation") |
