| schema_version: 1 |
| id: EIDORA/ResNet50_IN1k |
| name: ResNet50_IN1k |
| version: 1.0.0 |
| model_family: ResNet |
| backend: onnx |
| file_size: 94 MB |
| runtime: |
| adapter: onnx_image |
| execution_provider: CPUExecutionProvider |
| model_path: model.onnx |
| input_names: |
| - pixel_values |
| output_name: embedding |
| onnxruntime: |
| opset: 17 |
| tested_versions: '>=1.17,<2' |
| artifact: |
| path: model.onnx |
| sha256: 09c59c1eba07408c5174b5fd58774bd16495cf0503f0406b0accfb2502ae6df0 |
| package_size_bytes: 93951417 |
| inputs: |
| - id: image |
| modality: image |
| label: Images |
| required: true |
| source_kind: media_source |
| requirements: |
| color_space: RGB |
| layout: NCHW |
| width: 224 |
| height: 224 |
| preprocess: |
| image: |
| resize_mode: |
| label: Image preprocessing |
| kind: choice |
| choices: |
| - distort |
| - crop_center |
| - add_padding |
| default: crop_center |
| visible: true |
| resize: |
| mode: resize_shorter_edge_then_center_crop |
| resize_size: 256 |
| crop_width: 224 |
| crop_height: 224 |
| interpolation: bilinear |
| source: TorchVision ResNet50_Weights.IMAGENET1K_V2.transforms |
| rescale: 1/255 |
| normalize: |
| mean: |
| - 0.485 |
| - 0.456 |
| - 0.406 |
| std: |
| - 0.229 |
| - 0.224 |
| - 0.225 |
| inside_onnx: true |
| embedding: |
| dimensions: 2048 |
| feature_type: embedding |
| pooling: feature_layer |
| normalized: true |
| similarity: cosine |
| output_name: embedding |
| dtype: float32 |
| shape: |
| - batch |
| - 2048 |
| display: |
| summary: 'Medium: reliable ImageNet visual embeddings with moderate CPU runtime.' |
| compute_tier: medium |
| modality_labels: |
| - image |
| recommended_batch_size: 8 |
| validation: |
| fixtures: |
| - id: image_tensor_001 |
| input_shape: |
| - 1 |
| - 3 |
| - 224 |
| - 224 |
| expected_shape: |
| - 1 |
| - 2048 |
| seed: 51 |
| checks: |
| load_with: onnxruntime |
| execution_provider: CPUExecutionProvider |
| output_dtype: float32 |
| finite: true |
| normalized_l2_range: |
| - 0.99 |
| - 1.01 |
| provenance: |
| base_model: torchvision/resnet50-imagenet1k-v2 |
| source_repository: https://pytorch.org/vision/stable/models/generated/torchvision.models.resnet50.html |
| original_model_name: ResNet-50 ImageNet |
| original_model_url: https://github.com/pytorch/vision |
| authors: |
| - Kaiming He |
| - Xiangyu Zhang |
| - Shaoqing Ren |
| - Jian Sun |
| paper_title: Deep Residual Learning for Image Recognition |
| paper_url: https://arxiv.org/abs/1512.03385 |
| upstream_license: BSD-3-Clause for TorchVision code; ImageNet weights are distributed |
| by PyTorch under documented model terms. |
| training_data: ImageNet-1K supervised classification data. |
| citation: "@inproceedings{he2016deep,\n title={Deep Residual Learning for Image\ |
| \ Recognition},\n author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and\ |
| \ Sun, Jian},\n booktitle={CVPR},\n year={2016}\n}\n" |
| conversion_note: EIDORA produced this ONNX conversion and is not the original model |
| creator. |
| export_date: '2026-07-14' |
| exporter_version: eidora-onnx-exporter 0.1.0 |
| model_card: |
| best_for: |
| - General image grouping and retrieval. |
| - Projects that need a well-established visual baseline. |
| not_ideal_for: |
| - Text, video, or audio inputs. |
| - Fine-grained semantic retrieval where self-supervised models are preferred. |
| limitations: ResNet-50 is trained for ImageNet classification, so its embeddings |
| may underperform specialized or self-supervised models on some visual domains. |
| license: |
| id: bsd-3-clause |
| attribution: Converted to ONNX for EIDORA from TorchVision ResNet-50 ImageNet |
| weights. |
| huggingface: |
| org: eidora |
| repo_name: RESNET50_2048 |
| pipeline_tag: feature-extraction |
| tags: |
| - eidora |
| - eidora-model-zoo |
| - onnx |
| - onnxruntime |
| - embeddings |
| - image |
| - resnet |
| - compute:medium |
| - modality:image |
| datasets: |
| - imagenet-1k |
| metrics: |
| - cosine-similarity |
|
|
