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README.md

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+---
+dataset_info:
+- config_name: corpus
+  features:
+  - name: corpus-id
+    dtype: string
+  - name: image
+    dtype: image
+  splits:
+  - name: train
+    num_bytes: 315479652.451
+    num_examples: 9593
+  download_size: 289013318
+  dataset_size: 315479652.451
+- config_name: qrels
+  features:
+  - name: query-id
+    dtype: string
+  - name: corpus-id
+    dtype: string
+  - name: score
+    dtype: int32
+  splits:
+  - name: train
+    num_bytes: 353706
+    num_examples: 11307
+  download_size: 185552
+  dataset_size: 353706
+- config_name: queries
+  features:
+  - name: query-id
+    dtype: string
+  - name: query
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: options
+    sequence: string
+  - name: is_numerical
+    dtype: int32
+  splits:
+  - name: train
+    num_bytes: 1485381
+    num_examples: 11307
+  download_size: 507845
+  dataset_size: 1485381
+configs:
+- config_name: corpus
+  data_files:
+  - split: train
+    path: corpus/train-*
+- config_name: qrels
+  data_files:
+  - split: train
+    path: qrels/train-*
+- config_name: queries
+  data_files:
+  - split: train
+    path: queries/train-*
+---
+
+## Dataset Description
+This is a VQA dataset based on Scientific Plots from PlotQA dataset from [PlotQA](https://arxiv.org/abs/1909.00997).
+
+### Load the dataset 
+```python
+from datasets import load_dataset
+import csv
+
+def load_beir_qrels(qrels_file):
+    qrels = {}
+    with open(qrels_file) as f:
+        tsvreader = csv.DictReader(f, delimiter="\t")
+        for row in tsvreader:
+            qid = row["query-id"]
+            pid = row["corpus-id"]
+            rel = int(row["score"])
+            if qid in qrels:
+                qrels[qid][pid] = rel
+            else:
+                qrels[qid] = {pid: rel}
+    return qrels
+
+corpus_ds = load_dataset("openbmb/VisRAG-Ret-Test-PlotQA", name="corpus", split="train")
+queries_ds = load_dataset("openbmb/VisRAG-Ret-Test-PlotQA", name="queries", split="train")
+
+qrels_path = "xxxx" # path to qrels file which can be found under qrels folder in the repo.
+qrels = load_beir_qrels(qrels_path)
+```
+

corpus/train-00000-of-00001.parquet

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