Update README.md

README.md

@@ -2,4 +2,62 @@
 license: other
 license_name: adobe-research-license
 license_link: LICENSE
+language:
+- en
 ---
+# [ICML 2025] Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage
+
+This dataset is associated with the evaluation in our ICML 2025 paper, [Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage](https://arxiv.org/abs/2412.15484).
+
+## Prerequisites
+### Packages
+* openai>=1.14.1
+* python-dotenv==1.0.1
+
+### Dataset download
+```dataset download
+from huggingface_hub import hf_hub_download
+
+local_path = hf_hub_download(
+    repo_id="saehyungl/CapMAS",
+    filename="images_capmas.tar.gz",
+    repo_type="dataset"
+)
+print("Downloaded to:", local_path)
+```
+Or you can download it using [this URL](https://huggingface.co/datasets/saehyungl/CapMAS/resolve/main/images_capmas.tar.gz?download=true).
+Our evaluation uses a subset of the [DOCCI](https://google.github.io/docci/) images.
+
+## Captioning
+Please generate captions for the 1,000 downloaded images for captioning evaluation.
+Summarize the generated captions into a dictionary where the key is the corresponding image file name, and save it as a .json file.
+```captions file
+{
+    "aar_test_04600.jpg": <caption_aar_test_04600>,
+    "aar_test_04601.jpg": <caption_aar_test_04601>,
+    ...
+    "test_00599.json": <caption_test_00599>,
+}
+```
+You may refer to the [sample captions](https://github.com/david-yoon/CapMAS_private/blob/main/sample_captions/llava1.6-vicuna_llama3_th1.0/captions_final.json) for guidance.
+
+## Evaluation
+Please visit our [GitHub repository](https://github.com/david-yoon/CapMAS_private).
+We provide the evaluation codes for the three metrics used in our paper: **Factuality**, **Coverage**, and **CLAIR** (Chan et al., EMNLP 2023). These evaluations rely on GPT-4o, so please fill in your OpenAI API key **OR** Azure OpenAI credentials in the `conf/gpt4o` file.
+### Factuality (ours)
+```factuality
+python eval_factuality.py --image-dir <the image directory path> --captions-file <the caption .json file path>
+```
+### Coverage (ours)
+```coverage
+python eval_coverage.py --vqa-dir data/COVERAGE_TEST_VQA --captions-file <the caption .json file path>
+```
+### CLAIR
+```clair
+python eval_clair.py --captions-file <the caption .json file path>
+```
+
+## References
+1. [DOCCI (Onoe et al., ECCV 2024)](https://google.github.io/docci/#downloads)
+2. [ImageInWords (Garg et al., EMNLP 2024)](https://github.com/google/imageinwords)
+3. [CLAIR (Chan et al., EMNLP 2023)](https://github.com/davidmchan/clair)