Instructions to use GOH-SIM-YNG-NICOLE/DETR_ObjectDetect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GOH-SIM-YNG-NICOLE/DETR_ObjectDetect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="GOH-SIM-YNG-NICOLE/DETR_ObjectDetect")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("GOH-SIM-YNG-NICOLE/DETR_ObjectDetect") model = AutoModel.from_pretrained("GOH-SIM-YNG-NICOLE/DETR_ObjectDetect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "/content/drive/MyDrive/C3879C_Capstone_Project/23042499-GohSimYngNicole-C3879C-AY23T4CP/DETR", | |
| "activation_dropout": 0.0, | |
| "activation_function": "relu", | |
| "architectures": [ | |
| "DetrModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auxiliary_loss": false, | |
| "backbone": "resnet50", | |
| "backbone_config": null, | |
| "bbox_cost": 5, | |
| "bbox_loss_coefficient": 5, | |
| "class_cost": 1, | |
| "classifier_dropout": 0.0, | |
| "d_model": 256, | |
| "decoder_attention_heads": 8, | |
| "decoder_ffn_dim": 2048, | |
| "decoder_layerdrop": 0.0, | |
| "decoder_layers": 6, | |
| "dice_loss_coefficient": 1, | |
| "dilation": false, | |
| "do_normalize": true, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "dropout": 0.1, | |
| "encoder_attention_heads": 8, | |
| "encoder_ffn_dim": 2048, | |
| "encoder_layerdrop": 0.0, | |
| "encoder_layers": 6, | |
| "eos_coefficient": 0.1, | |
| "format": "coco_detection", | |
| "giou_cost": 2, | |
| "giou_loss_coefficient": 2, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2", | |
| "3": "LABEL_3", | |
| "4": "LABEL_4", | |
| "5": "LABEL_5", | |
| "6": "LABEL_6", | |
| "7": "LABEL_7" | |
| }, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "DetrImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "init_std": 0.02, | |
| "init_xavier_std": 1.0, | |
| "is_encoder_decoder": true, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2, | |
| "LABEL_3": 3, | |
| "LABEL_4": 4, | |
| "LABEL_5": 5, | |
| "LABEL_6": 6, | |
| "LABEL_7": 7 | |
| }, | |
| "mask_loss_coefficient": 1, | |
| "max_position_embeddings": 1024, | |
| "model_type": "detr", | |
| "num_channels": 3, | |
| "num_hidden_layers": 6, | |
| "num_queries": 100, | |
| "position_embedding_type": "sine", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "scale_embedding": false, | |
| "size": { | |
| "longest_edge": 1333, | |
| "shortest_edge": 800 | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.35.2", | |
| "use_pretrained_backbone": true, | |
| "use_timm_backbone": true | |
| } | |