Update README.md

README.md

@@ -1,72 +1,217 @@
 ---
+base_model: timm/resnet18d.ra2_in1k
+base_model_relation: merge
 library_name: segmentation-models-pytorch
-license: mit
+license: cc-by-4.0
+metrics:
+- accuracy
+- confusion_matrix
+- f1
+- mean_iou
+- precision
+- recall
 pipeline_tag: image-segmentation
 tags:
-- model_hub_mixin
-- pytorch_model_hub_mixin
-- segmentation-models-pytorch
+- aerial-imagery
+- lidar
+- data-fusion
+- roofing-materials
+- roofing-material-classification
 - semantic-segmentation
-- pytorch
-languages:
-- python
 ---
-# DeepLabV3Plus Model Card
-
-Table of Contents:
-- [Load trained model](#load-trained-model)
-- [Model init parameters](#model-init-parameters)
-- [Model metrics](#model-metrics)
-- [Dataset](#dataset)
-
-## Load trained model
-```python
-import segmentation_models_pytorch as smp
-
-model = smp.from_pretrained("<save-directory-or-this-repo>")
-```
-
-## Model init parameters
-```python
-model_init_params = {
-    "encoder_name": "tu-resnet18d",
-    "encoder_depth": 5,
-    "encoder_weights": "imagenet",
-    "encoder_output_stride": 16,
-    "decoder_channels": 256,
-    "decoder_atrous_rates": (20, 15, 6),
-    "decoder_aspp_separable": True,
-    "decoder_aspp_dropout": 0,
-    "in_channels": 10,
-    "classes": 9,
-    "activation": None,
-    "upsampling": 4,
-    "aux_params": None,
-    "global_pool": "avgmax",
-    "drop_rate": 0.030244232449387346,
-    "drop_path_rate": 0.43231510659674255,
-    "zero_init_last": True,
-    "block_args": {'attn_layer': 'eca'}
-}
-```
-
-## Model metrics
-```json
-[
-    "accuracy",
-    "confusion_matrix",
-    "f1",
-    "mean_iou",
-    "precision",
-    "recall"
-]
-```
-
-## Dataset
-Dataset name: [More Information Needed]
-
-## More Information
-- Library: https://github.com/qubvel/segmentation_models.pytorch
-- Docs: https://smp.readthedocs.io/en/latest/
-
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin)
+
+# Model Card for RoofSense
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+An encoder-decoder semantic segmentation model for multimodal roofing material classification.
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+The model adopts an encoder-decoder architecture, pairing ResNet-18-D with DeepLabv3+.
+Following hyperparameter optimisation, the encoder blocks were augmented with anti-aliasing and efficient channel attention modules.
+In addition, the global average pooling blocks in the encoder were replaced with the mean of average and maximum pooling.
+Furthermore, dilation rates of the atrous spatial pyramid pooling block of the decoder were set to $\left(20, 15, 6\right)$.
+Finally, address any labelling errors and improve predicitions in small regions, the decorer output stride was set to sixteen.
+
+- **Developed by:** Dimitris Mantas, Delft University of Technology, The Netherlands
+- **Model type:** Fully Convolutional Neural Network
+- **License:** Creative Commons Attribution 4.0 International
+- **Base Model:** timm/resnet18d.ra2_in1k (Transfer Learning)
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** https://github.com/DimitrisMantas/RoofSense
+- **Resources:** https://repository.tudelft.nl/record/uuid:c463e920-61e6-40c5-89e9-25354fadf549
+
+<!-- TODO -->
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+{{ direct_use | default("[More Information Needed]", true)}}
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+{{ downstream_use | default("[More Information Needed]", true)}}
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+{{ out_of_scope_use | default("[More Information Needed]", true)}}
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+{{ bias_risks_limitations | default("[More Information Needed]", true)}}
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+{{ bias_recommendations | default("Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.", true)}}
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+{{ get_started_code | default("[More Information Needed]", true)}}
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+{{ training_data | default("[More Information Needed]", true)}}
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+{{ preprocessing | default("[More Information Needed]", true)}}
+
+
+#### Training Hyperparameters
+
+- **Training regime:** {{ training_regime | default("[More Information Needed]", true)}} <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+{{ speeds_sizes_times | default("[More Information Needed]", true)}}
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+{{ testing_data | default("[More Information Needed]", true)}}
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+{{ testing_factors | default("[More Information Needed]", true)}}
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+{{ testing_metrics | default("[More Information Needed]", true)}}
+
+### Results
+
+{{ results | default("[More Information Needed]", true)}}
+
+#### Summary
+
+{{ results_summary | default("", true) }}
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+{{ model_examination | default("[More Information Needed]", true)}}
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** {{ hardware_type | default("[More Information Needed]", true)}}
+- **Hours used:** {{ hours_used | default("[More Information Needed]", true)}}
+- **Cloud Provider:** {{ cloud_provider | default("[More Information Needed]", true)}}
+- **Compute Region:** {{ cloud_region | default("[More Information Needed]", true)}}
+- **Carbon Emitted:** {{ co2_emitted | default("[More Information Needed]", true)}}
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+{{ model_specs | default("[More Information Needed]", true)}}
+
+### Compute Infrastructure
+
+{{ compute_infrastructure | default("[More Information Needed]", true)}}
+
+#### Hardware
+
+{{ hardware_requirements | default("[More Information Needed]", true)}}
+
+#### Software
+
+{{ software | default("[More Information Needed]", true)}}
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+{{ citation_bibtex | default("[More Information Needed]", true)}}
+
+**APA:**
+
+{{ citation_apa | default("[More Information Needed]", true)}}
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+{{ glossary | default("[More Information Needed]", true)}}
+
+## More Information [optional]
+
+{{ more_information | default("[More Information Needed]", true)}}
+
+## Model Card Authors [optional]
+
+{{ model_card_authors | default("[More Information Needed]", true)}}
+
+## Model Card Contact
+
+{{ model_card_contact | default("[More Information Needed]", true)}}