chore: checkpoint

Signed-off-by: ivelin <[email protected]>

ui_refexp.py

@@ -21,7 +21,7 @@ import os
 import tensorflow as tf
 import re
 import datasets
-
+import json
 import numpy as np
 
 # Find for instance the citation on arxiv or on the dataset repo/website
@@ -68,7 +68,7 @@ _METADATA_URLS = {
 def tfrecord2list(tfr_file: None):
     """Filter and convert refexp tfrecord file to a list of dict object.
     Each sample in the list is a dict with the following keys: (image_id, prompt, target_bounding_box)"""
-    test_raw_dataset = tf.data.TFRecordDataset([tfr_file])
+    raw_tfr_dataset = tf.data.TFRecordDataset([tfr_file])
     count = 0
     donut_refexp_dict = []
     for raw_record in raw_tfr_dataset:
@@ -141,8 +141,8 @@ class UIRefExp(datasets.GeneratorBasedBuilder):
                 "screenshot": datasets.Image(),
                 # click the search button next to menu drawer at the top of the screen
                 "prompt": datasets.Value("string"),
-                # [xmin, ymin, xmax, ymax], normalized screen reference values between 0 and 1
-                "target_bounding_box": dict,
+                # json: {xmin, ymin, xmax, ymax}, normalized screen reference values between 0 and 1
+                "target_bounding_box": datasets.Value("string"),
             }
         )
 
@@ -215,13 +215,25 @@ class UIRefExp(datasets.GeneratorBasedBuilder):
 
         metadata = tfrecord2list(metadata_file)
         files_to_keep = set()
+        image_labels = {}
         for sample in metadata:
-            files_to_keep.add(sample["image_id"])
+            image_id = sample["image_id"]
+            files_to_keep.add(image_id)
+            labels = image_labels.get(image_id)
+            if isinstance(labels, list):
+                labels.append(sample)
+            else:
+                labels = [sample]
+                image_labels[image_id] = labels
         for file_path, file_obj in images:
-            image_id = file_path.search("(\d+).jpg").group(1)
-            if image_id and image_id in files_to_keep:
-                label = file_path.split("/")[2]
-                yield file_path, {
-                    "image": {"path": file_path, "bytes": file_obj.read()},
-                    "label": label,
-                }
+            image_id = re.search("(\d+).jpg", file_path)
+            if image_id:
+                image_id = image_id.group(1)
+                if image_id in files_to_keep:
+                    for labels in image_labels[image_id]:
+                        bb_json = json.dumps(labels["target_bounding_box"])
+                        yield file_path, {
+                            "screenshot": {"path": file_path, "bytes": file_obj.read()},
+                            "prompt": labels["prompt"],
+                            "target_bounding_box": bb_json
+                        }