dataset uploaded by roboflow2huggingface package

README.md

@@ -21,7 +21,7 @@ tags:
 ### Number of Images
 
 ```json
-{'test': 37, 'train': 323, 'valid': 73}
+{'train': 323, 'valid': 73, 'test': 37}
 ```
 
 

crack-instance-segmentation.py

@@ -77,6 +77,7 @@ class CRACKINSTANCESEGMENTATION(datasets.GeneratorBasedBuilder):
                         "id": datasets.Value("int64"),
                         "area": datasets.Value("int64"),
                         "bbox": datasets.Sequence(datasets.Value("float32"), length=4),
+                        "segmentation": datasets.Sequence(datasets.Value("float32")),
                         "category": datasets.ClassLabel(names=_CATEGORIES),
                     }
                 ),
@@ -132,12 +133,12 @@ class CRACKINSTANCESEGMENTATION(datasets.GeneratorBasedBuilder):
         image_id_to_annotations = collections.defaultdict(list)
         for annot in annotations["annotations"]:
             image_id_to_annotations[annot["image_id"]].append(annot)
-        image_id_to_image = {annot["file_name"]: annot for annot in annotations["images"]}
+        filename_to_image = {annot["file_name"]: image for image in annotations["images"]}
 
         for filename in os.listdir(folder_dir):
             filepath = os.path.join(folder_dir, filename)
-            if filename in image_id_to_image:
-                image = image_id_to_image[filename]
+            if filename in filename_to_image:
+                image = filename_to_image[filename]
                 objects = [
                     process_annot(annot, category_id_to_category) for annot in image_id_to_annotations[image["id"]]
                 ]

data/test.zip

@@ -1,3 +1,3 @@
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-oid sha256:0b8e74948345eb41eba46e70331b16b85ec373c1c28e4fdbd9c8cd0d74b8bf2a
+oid sha256:d3606f619defe5633dd7e87377f33cb3b417c66eb2bfb5b34d44d4a287d59862
 size 1429165

data/train.zip

@@ -1,3 +1,3 @@
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-oid sha256:5c797753c4743b0d10aa5a390a4a54e09de1cc51958b0d9326946ec79de1aca7
+oid sha256:1f8a734c4ae9ce00d093cc34112bb88c5a65964f92b9ea3e2617b661a01ec29d
 size 10567198

data/valid-mini.zip

@@ -1,3 +1,3 @@
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-oid sha256:b4feef110accb74c7542eecdf2099a23e24a60afe85fb9e1b04bc2338debaef8
-size 138840
+oid sha256:b9c2b5205dbcda15149c1cf2a208ab4ac455980526781ec27dc4503c71414e34
+size 124533

data/valid.zip

@@ -1,3 +1,3 @@
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-oid sha256:1f1159a54a4b7233c5898638842fd75d23f0c08f7df740c3902569e4b5027575
+oid sha256:d695085c716f23b3baaf5199b66aa7058cdb7caf7587794621d0da64267e9513
 size 2306229

split_name_to_num_samples.json

@@ -1 +1 @@
-{"test": 37, "train": 323, "valid": 73}
+{"train": 323, "valid": 73, "test": 37}