Upload Mask2FormerForUniversalSegmentation
Browse files- README.md +199 -0
- config.json +235 -0
- model.safetensors +3 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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config.json
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{
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"_name_or_path": "mouadenna/mask2former-swin-base-ade-PV-segmentation-66iou",
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"activation_function": "relu",
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"architectures": [
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"Mask2FormerForUniversalSegmentation"
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],
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"backbone": null,
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"backbone_config": {
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"depths": [
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2,
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2,
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18,
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2
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],
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"drop_path_rate": 0.3,
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"embed_dim": 128,
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"hidden_size": 1024,
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"model_type": "swin",
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"num_heads": [
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4,
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8,
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16,
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32
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],
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"out_features": [
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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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"out_indices": [
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1,
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2,
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3,
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4
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],
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"path_norm": true,
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"window_size": 12
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},
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"backbone_kwargs": null,
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"class_weight": 2.0,
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"common_stride": 4,
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"decoder_layers": 10,
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"dice_weight": 5.0,
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"dim_feedforward": 2048,
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"dropout": 0.0,
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"encoder_feedforward_dim": 1024,
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"encoder_layers": 6,
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"enforce_input_proj": false,
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"enforce_input_projection": false,
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"feature_size": 256,
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"feature_strides": [
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4,
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8,
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16,
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32
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],
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"hidden_dim": 256,
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"id2label": {
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"0": "unlabeled",
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"1": "PV"
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},
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"ignore_value": 255,
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"importance_sample_ratio": 0.75,
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"init_std": 0.02,
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"init_xavier_std": 1.0,
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"label2id": {
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"airplane": 90,
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"animal": 126,
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"apparel": 92,
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"arcade machine": 78,
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"armchair": 30,
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"ashcan": 138,
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"awning": 86,
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"bag": 115,
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"ball": 119,
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"bannister": 95,
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"bar": 77,
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"barrel": 111,
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"base": 40,
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"basket": 112,
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"bathtub": 37,
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"bed ": 7,
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"bench": 69,
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"bicycle": 127,
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"blanket": 131,
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"blind": 63,
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"boat": 76,
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"book": 67,
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"bookcase": 62,
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"booth": 88,
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"bottle": 98,
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"box": 41,
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"bridge": 61,
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"buffet": 99,
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"building": 1,
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"bulletin board": 144,
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"bus": 80,
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"cabinet": 10,
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"canopy": 106,
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"car": 20,
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"case": 55,
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"ceiling": 5,
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"chair": 19,
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"chandelier": 85,
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"chest of drawers": 44,
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"clock": 148,
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"coffee table": 64,
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"column": 42,
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"computer": 74,
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"conveyer belt": 105,
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"counter": 45,
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"countertop": 70,
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"cradle": 117,
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"crt screen": 141,
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"curtain": 18,
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"cushion": 39,
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"desk": 33,
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"dirt track": 91,
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"dishwasher": 129,
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"door": 14,
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+
"earth": 13,
|
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|
124 |
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|
125 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
196 |
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|
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|
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|
199 |
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"tank": 122,
|
200 |
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"television receiver": 89,
|
201 |
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"tent": 114,
|
202 |
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"toilet": 65,
|
203 |
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"towel": 81,
|
204 |
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"tower": 84,
|
205 |
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"trade name": 123,
|
206 |
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"traffic light": 136,
|
207 |
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"tray": 137,
|
208 |
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"tree": 4,
|
209 |
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"truck": 83,
|
210 |
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"van": 102,
|
211 |
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"vase": 135,
|
212 |
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"wall": 0,
|
213 |
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"wardrobe": 35,
|
214 |
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"washer": 107,
|
215 |
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"water": 21,
|
216 |
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"waterfall": 113,
|
217 |
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"windowpane": 8
|
218 |
+
},
|
219 |
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"mask_feature_size": 256,
|
220 |
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"mask_weight": 5.0,
|
221 |
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"model_type": "mask2former",
|
222 |
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"no_object_weight": 0.1,
|
223 |
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"num_attention_heads": 8,
|
224 |
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"num_hidden_layers": 10,
|
225 |
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"num_queries": 100,
|
226 |
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"output_auxiliary_logits": null,
|
227 |
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"oversample_ratio": 3.0,
|
228 |
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"pre_norm": false,
|
229 |
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"torch_dtype": "float32",
|
230 |
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"train_num_points": 12544,
|
231 |
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"transformers_version": "4.43.0.dev0",
|
232 |
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"use_auxiliary_loss": true,
|
233 |
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"use_pretrained_backbone": false,
|
234 |
+
"use_timm_backbone": false
|
235 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:22ea980c517b1696859428caf3c266ddfb8f33f547872251bf8a4a09c7d3bd3c
|
3 |
+
size 431632856
|