Upload old datasets as a v0 version

As titled, we update the original dataset.

.gitattributes

@@ -56,3 +56,11 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+VHs_full/multi_needle/visual_haystack_1000.json filter=lfs diff=lfs merge=lfs -text
+VHs_full/multi_needle/visual_haystack_10000.json filter=lfs diff=lfs merge=lfs -text
+VHs_full/multi_needle/visual_haystack_500.json filter=lfs diff=lfs merge=lfs -text
+VHs_full/single_needle/visual_haystack_1000.json filter=lfs diff=lfs merge=lfs -text
+VHs_full/single_needle/visual_haystack_10000.json filter=lfs diff=lfs merge=lfs -text
+VHs_full/single_needle/visual_haystack_500.json filter=lfs diff=lfs merge=lfs -text
+VHs_small/multi_needle/visual_haystack_10000.json filter=lfs diff=lfs merge=lfs -text
+VHs_small/single_needle/visual_haystack_10000.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,38 @@
----
-license: mit
----
+---
+license: mit
+---
+
+# Visual Haystacks Dataset Card
+
+## Dataset details
+1. Dataset type: Visual Haystacks (VHs) is a benchmark dataset specifically designed to evaluate the Large Multimodal Model's (LMM's) capability to handle long-context visual information. It can also be viewed as the first visual-centric Needle-In-A-Haystack (NIAH) benchmark dataset. Please also download COCO-2017's training set validation set.
+
+2. Data Preparation and Benchmarking
+  - Download the VQA questions:
+    ```
+    huggingface-cli download --repo-type dataset tsunghanwu/visual_haystacks --local-dir dataset/VHs_qa
+    ```
+  - Download the COCO 2017 dataset and organize it as follows, with the default root directory ./dataset/coco:
+    ```
+    dataset/
+    ├── coco
+    │   ├── annotations
+    │   ├── test2017
+    │   └── val2017
+    └── VHs_qa
+        ├── VHs_full
+        │   ├── multi_needle
+        │   └── single_needle
+        └── VHs_small
+            ├── multi_needle
+            └── single_needle
+    ```
+  - Follow the instructions in https://github.com/visual-haystacks/vhs_benchmark to run the evaluation
+
+
+3. Please check out our [project page](https://visual-haystacks.github.io) for more information. You can also send questions or comments about the model to [our github repo](https://github.com/visual-haystacks/vhs_benchmark/issues)
+
+## Intended use
+Primary intended uses: The primary use of VHs is research on large multimodal models and chatbots.
+
+Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.

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VHs_small/multi_needle/visual_haystack_10.json

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VHs_small/multi_needle/visual_haystack_5.json

@@ -0,0 +1 @@
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VHs_small/multi_needle/visual_haystack_oracle.json

@@ -0,0 +1 @@
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VHs_small/single_needle/visual_haystack_10.json

@@ -0,0 +1 @@
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VHs_small/single_needle/visual_haystack_20.json

@@ -0,0 +1 @@
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VHs_small/single_needle/visual_haystack_3.json

@@ -0,0 +1 @@
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VHs_small/single_needle/visual_haystack_5.json

@@ -0,0 +1 @@
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VHs_small/single_needle/visual_haystack_oracle.json

@@ -0,0 +1 @@
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