test new feature definition without json

dataset_infos.json

@@ -4,36 +4,6 @@
     "citation": "@inproceedings{harley2015icdar,\n    title = {Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval},\n    author = {Adam W Harley and Alex Ufkes and Konstantinos G Derpanis},\n    booktitle = {International Conference on Document Analysis and Recognition ({ICDAR})}},\n    year = {2015}\n}\n",
     "homepage": "https://www.cs.cmu.edu/~aharley/rvl-cdip/",
     "license": "https://www.industrydocuments.ucsf.edu/help/copyright/",
-    "features": {
-      "image": {
-        "decode": true,
-        "id": null,
-        "_type": "Image"
-      },
-      "label": {
-        "num_classes": 16,
-        "names": [
-          "letter",
-          "form",
-          "email",
-          "handwritten",
-          "advertisement",
-          "scientific report",
-          "scientific publication",
-          "specification",
-          "file folder",
-          "news article",
-          "budget",
-          "invoice",
-          "presentation",
-          "questionnaire",
-          "resume",
-          "memo"
-        ],
-        "id": null,
-        "_type": "ClassLabel"
-      }
-    },
     "post_processed": null,
     "supervised_keys": {
       "input": "image",

rvl_cdip_easyOCR.py

@@ -88,6 +88,8 @@ class RvlCdip(datasets.GeneratorBasedBuilder):
                     "id": datasets.Value("string"),
                     "image": datasets.Image(),
                     "label": datasets.ClassLabel(names=_CLASSES),
+                    "words": datasets.Sequence(datasets.Value("string")),
+                    "boxes": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
                 }
             ),
             supervised_keys=("image", "label"),
@@ -171,10 +173,10 @@ class RvlCdip(datasets.GeneratorBasedBuilder):
     @staticmethod
     def _path_to_OCR(image_to_OCR, file_path):
         # obtain text and boxes given file_path
-        text, boxes = None, None
+        words, boxes = None, None
         if file_path in image_to_OCR:
-            text, boxes = image_to_OCR[file_path]
-        return text, boxes
+            words, boxes = image_to_OCR[file_path]
+        return words, boxes
 
     def _generate_examples(self, archive_iterator, labels_filepath, split):
         with open(labels_filepath, encoding="utf-8") as f:

test_loader.py

@@ -1,5 +1,18 @@
 from datasets import load_dataset
 
+
+data = load_dataset(
+    "jordyvl/rvl-cdip_easyOCR",
+    split="test",
+    #cache_dir="/mnt/lerna/data/HFcache",
+    # data_files={ # this is the path to the images if it does not download it
+    #     "binary": __file__#"/mnt/lerna/data/HFcache/downloads/c8cc6f89129255a9adf3e97e319ebe2055cf97662135b3ad26c79e9432544db5",
+    # },
+    #data_dir="/home/jordy/Downloads/OCRedText", # this is the path to the OCR data
+)
+from pdb import set_trace; set_trace()
+
+
 data = load_dataset(
     "./rvl_cdip_easyOCR.py",
     split="test",