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add upcoming webinar banner (#82)
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@frederik-encord
frederik-encord authored Jul 10, 2024
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<h1 align="center">
<a href="https://encord.com/webinar/tti-eval-webinar/">
<img src="https://storage.googleapis.com/docs-media.encord.com/static/img/text-to-image-eval/fint-tune-text-to-image.jpg" alt="tti-eval logo banner">
</a>
</h1>

<div align="center" style="display: flex; justify-content: space-between;">
<div style="flex: 1; padding: 10px;">
<a href="https://colab.research.google.com/github/encord-team/text-to-image-eval/blob/main/notebooks/tti_eval_CLI_Quickstart.ipynb" target="_blank" style="text-decoration:none"><img alt="CLI Quickstart In Colab" src="https://img.shields.io/badge/Try_It_In_Colab-blue?logo=googlecolab&labelColor=555"></a>
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> <img alt="Python Quickstart In Colab" src="https://img.shields.io/badge/Python_Quickstart_In_Colab-blue?logo=googlecolab&labelColor=555">
> </a>

## Some Example Results

One example of where this `tti-eval` is useful is to test different open-source models against different open-source datasets within a specific domain.
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### Weighted KNN Accuracy

| Model/Dataset | Alzheimer-MRI | LungCancer4Types | chest-xray-classification | skin-cancer |
|:-----------------|:-------------:|:----------------:|:-------------------------:|:-----------:|
| :--------------- | :-----------: | :--------------: | :-----------------------: | :---------: |
| apple | 0.6777 | 0.6633 | 0.9687 | 0.7985 |
| bioclip | 0.8952 | 0.7800 | 0.9771 | 0.7961 |
| clip | 0.6986 | 0.6867 | 0.9727 | 0.7891 |
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### Zero-shot Accuracy

| Model/Dataset | Alzheimer-MRI | LungCancer4Types | chest-xray-classification | skin-cancer |
|:-----------------|:-------------:|:----------------:|:-------------------------:|:-----------:|
| :--------------- | :-----------: | :--------------: | :-----------------------: | :---------: |
| apple | 0.4460 | 0.2367 | 0.7381 | 0.3594 |
| bioclip | 0.3092 | 0.2200 | 0.7356 | 0.0431 |
| clip | 0.4857 | 0.2267 | 0.7381 | 0.1955 |
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### Image-to-image Retrieval

| Model/Dataset | Alzheimer-MRI | LungCancer4Types | chest-xray-classification | skin-cancer |
|:-----------------|:-------------:|:----------------:|:-------------------------:|:-----------:|
| :--------------- | :-----------: | :--------------: | :-----------------------: | :---------: |
| apple | 0.4281 | 0.2786 | 0.8835 | 0.6437 |
| bioclip | 0.4535 | 0.3496 | 0.8786 | 0.6278 |
| clip | 0.4247 | 0.2812 | 0.8602 | 0.6347 |
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### Linear Probe Accuracy

| Model/Dataset | Alzheimer-MRI | LungCancer4Types | chest-xray-classification | skin-cancer |
|:-----------------|:-------------:|:----------------:|:-------------------------:|:-----------:|
| :--------------- | :-----------: | :--------------: | :-----------------------: | :---------: |
| apple | 0.5482 | 0.5433 | 0.9362 | 0.7662 |
| bioclip | 0.6139 | 0.6600 | 0.9433 | 0.7933 |
| clip | 0.5547 | 0.5700 | 0.9362 | 0.7704 |
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> ⚠️ Currently, only image and image groups datasets are supported, with potential for future expansion to include video datasets.
| Dataset Title | Implementation | HF Dataset |
|:--------------------------|:--------------------------------|:-------------------------------------------------------------------------------------|
| :------------------------ | :------------------------------ | :----------------------------------------------------------------------------------- |
| Alzheimer-MRI | [Hugging Face][hf-dataset-impl] | [Falah/Alzheimer_MRI][Falah/Alzheimer_MRI] |
| chest-xray-classification | [Hugging Face][hf-dataset-impl] | [trpakov/chest-xray-classification][trpakov/chest-xray-classification] |
| LungCancer4Types | [Hugging Face][hf-dataset-impl] | [Kabil007/LungCancer4Types][Kabil007/LungCancer4Types] |
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### Hugging Face Models

| Model Title | Implementation | HF Model |
|:-----------------|:------------------------------|:-----------------------------------------------------------------------------------------------|
| :--------------- | :---------------------------- | :--------------------------------------------------------------------------------------------- |
| apple | [OpenCLIP][open-model-impl] | [apple/DFN5B-CLIP-ViT-H-14][apple/DFN5B-CLIP-ViT-H-14] |
| bioclip | [OpenCLIP][open-model-impl] | [imageomics/bioclip][imageomics/bioclip] |
| eva-clip | [OpenCLIP][open-model-impl] | [BAAI/EVA-CLIP-8B-448][BAAI/EVA-CLIP-8B-448] |
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### Locally Trained Models

| Model Title | Implementation | Weights |
|:-------------|:----------------------------------|:--------|
| :----------- | :-------------------------------- | :------ |
| rsicd-encord | [LocalOpenCLIP][local-model-impl] | - |

### Add a Model from a Known Source
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