Instructions to use PekingU/rtdetr_r34vd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PekingU/rtdetr_r34vd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="PekingU/rtdetr_r34vd")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("PekingU/rtdetr_r34vd") model = AutoModelForObjectDetection.from_pretrained("PekingU/rtdetr_r34vd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add config from convert_rt_detr_original_pytorch_checkpoint_to_pytorch.py
Browse files- config.json +35 -12
config.json
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": true,
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"backbone": "resnet34d",
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"backbone_config": null,
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"backbone_kwargs": {
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"features_only": true,
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"out_indices": [
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},
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"batch_norm_eps": 1e-05,
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"box_noise_scale": 1.0,
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"d_model": 256,
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],
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"decoder_layers": 4,
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"decoder_n_points": 4,
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"disable_custom_kernels": true,
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"dropout": 0.0,
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"encode_proj_layers": [
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],
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"focal_loss_alpha": 0.75,
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"focal_loss_gamma": 2.0,
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"hidden_expansion": 0.5,
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"id2label": {
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"0": "person",
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"1": "bicycle",
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},
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"label_noise_ratio": 0.5,
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"layer_norm_eps": 1e-05,
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"learn_initial_query": false,
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"matcher_alpha": 0.25,
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"matcher_bbox_cost": 5.0,
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"matcher_giou_cost": 2.0,
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"model_type": "rt_detr",
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"normalize_before": false,
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"num_denoising": 100,
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"num_feature_levels": 3,
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"num_queries": 300,
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"positional_encoding_temperature": 10000,
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"torch_dtype": "float32",
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"transformers_version": "4.42.0.dev0",
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"use_focal_loss": true,
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"use_pretrained_backbone": true,
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"use_timm_backbone": true,
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"weight_loss_bbox": 5.0,
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"weight_loss_giou": 2.0,
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"weight_loss_vfl": 1.0,
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],
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"attention_dropout": 0.0,
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"auxiliary_loss": true,
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"batch_norm_eps": 1e-05,
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"box_noise_scale": 1.0,
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"d_model": 256,
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],
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"decoder_layers": 4,
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"decoder_n_points": 4,
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"depths": [
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],
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"disable_custom_kernels": true,
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"downsample_in_bottleneck": false,
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"downsample_in_first_stage": false,
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"dropout": 0.0,
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"embedding_size": 64,
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"encode_proj_layers": [
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2
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],
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],
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"focal_loss_alpha": 0.75,
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"focal_loss_gamma": 2.0,
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"hidden_act": "relu",
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"hidden_expansion": 0.5,
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"hidden_sizes": [
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64,
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128,
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256,
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512
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],
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"id2label": {
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"0": "person",
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"1": "bicycle",
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},
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"label_noise_ratio": 0.5,
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"layer_norm_eps": 1e-05,
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"layer_type": "basic",
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"learn_initial_query": false,
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"matcher_alpha": 0.25,
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"matcher_bbox_cost": 5.0,
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"matcher_giou_cost": 2.0,
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"model_type": "rt_detr",
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"normalize_before": false,
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"num_channels": 3,
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"num_denoising": 100,
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"num_feature_levels": 3,
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"num_queries": 300,
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"out_features": [
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"stage2",
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"stage3",
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],
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"out_indices": [
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],
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"positional_encoding_temperature": 10000,
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4"
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],
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"torch_dtype": "float32",
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"transformers_version": "4.42.0.dev0",
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"use_focal_loss": true,
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"weight_loss_bbox": 5.0,
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"weight_loss_giou": 2.0,
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"weight_loss_vfl": 1.0,
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