Add datafiles.

.gitattributes

@@ -52,3 +52,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+train2017.zip filter=lfs diff=lfs merge=lfs -text
+val2017.zip filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,59 @@
 ---
 license: apache-2.0
 ---
+
+---
+dataset_info:
+- config_name: train
+  features:
+  - name: filename
+    dtype: string
+  - name: height
+    dtype: int64
+  - name: width
+    dtype: int64
+  - name: ann
+    struct:
+    - name: bboxes
+      sequence:
+        sequence: float64
+    - name: bboxes_ignore
+      sequence:
+        sequence: int64
+    - name: label_ignore
+      sequence: int64
+    - name: labels
+      sequence: int64
+  splits:
+  - name: train
+    num_bytes: 211748
+    num_examples: 500
+  download_size: 89624346
+  dataset_size: 211748
+- config_name: val
+  features:
+  - name: filename
+    dtype: string
+  - name: height
+    dtype: int64
+  - name: width
+    dtype: int64
+  - name: ann
+    struct:
+    - name: bboxes
+      sequence:
+        sequence: float64
+    - name: bboxes_ignore
+      sequence:
+        sequence: int64
+    - name: label_ignore
+      sequence: int64
+    - name: labels
+      sequence: int64
+  splits:
+  - name: val
+    num_bytes: 209868
+    num_examples: 500
+  download_size: 82654443
+  dataset_size: 209868
+---

tiny_coco.py

@@ -0,0 +1,113 @@
+import os
+
+import datasets
+from pycocotools.coco import COCO
+
+_DESCRIPTION = 'A tiny coco2017 dataset example.'
+
+_ROOT = 'https://huggingface.co/datasets/Apter/tiny-coco/'
+_URLS = {
+    'train': _ROOT + 'train2017.zip',
+    'train_meta': _ROOT + 'annotations/instances_train2017.json',
+    'val': _ROOT + 'val2017.zip',
+    'val_meta': _ROOT + 'annotations/instances_val2017.json',
+}
+
+_CLASSES = ('person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus',
+            'train', 'truck', 'boat', 'traffic light', 'fire hydrant',
+            'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog',
+            'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe',
+            'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
+            'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat',
+            'baseball glove', 'skateboard', 'surfboard', 'tennis racket',
+            'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl',
+            'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot',
+            'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
+            'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop',
+            'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven',
+            'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase',
+            'scissors', 'teddy bear', 'hair drier', 'toothbrush')
+
+
+class TinyCoco(datasets.GeneratorBasedBuilder):
+    """TODO: Short description of my dataset."""
+
+    VERSION = datasets.Version('0.1.0')
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name='train', version=VERSION, description='Training set'),
+        datasets.BuilderConfig(
+            name='val', version=VERSION, description='Validation set'),
+    ]
+    # It's not mandatory to have a default configuration.
+    # Just use one if it make sense.
+    DEFAULT_CONFIG_NAME = 'train'
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download(_URLS[self.config.name])
+        meta = dl_manager.download(_URLS[self.config.name + '_meta'])
+        return [
+            datasets.SplitGenerator(
+                name=self.config.name,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    'img_prefix': data_dir,
+                    'ann_file': meta
+                })
+        ]
+
+    def _generate_examples(self, img_prefix, ann_file):
+        """Parser coco format annotation file."""
+        coco = COCO(ann_file)
+        cat_ids = coco.getCatIds(_CLASSES)
+        cat2label = {cat_id: i for i, cat_id in enumerate(cat_ids)}
+        img_ids = coco.getImgIds()
+        index = 0
+        for i in img_ids:
+            sample = dict()
+            info = coco.loadImgs([i])[0]
+            sample['filename'] = os.path.join(img_prefix, info['file_name'])
+            sample['height'] = info['height']
+            sample['width'] = info['width']
+            ann_ids = coco.getAnnIds([i])
+            ann_info = coco.loadAnns(ann_ids)
+            gt_bboxes = []
+            gt_labels = []
+            gt_bboxes_ignore = []
+            gt_label_ignore = []
+            gt_masks_ann = []
+            for i, ann in enumerate(ann_info):
+                if ann.get('ignore', False):
+                    continue
+                x1, y1, w, h = ann['bbox']
+                inter_w = max(0, min(x1 + w, sample['width']) - max(x1, 0))
+                inter_h = max(0, min(y1 + h, sample['height']) - max(y1, 0))
+                if inter_w * inter_h == 0:
+                    continue
+                if ann['area'] <= 0 or w < 1 or h < 1:
+                    continue
+                if ann['category_id'] not in cat_ids:
+                    continue
+                bbox = [x1, y1, x1 + w, y1 + h]
+                if ann.get('iscrowd', False):
+                    gt_bboxes_ignore.append(bbox)
+                    gt_label_ignore.append(cat2label[ann['category_id']])
+                else:
+                    gt_bboxes.append(bbox)
+                    gt_labels.append(cat2label[ann['category_id']])
+                    gt_masks_ann.append(ann.get('segmentation', None))
+
+            sample['ann'] = dict(
+                bboxes=gt_bboxes,
+                labels=gt_labels,
+                bboxes_ignore=gt_bboxes_ignore,
+                label_ignore=gt_label_ignore)
+            yield index, sample
+            index += 1

train2017.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a8f8ea150f7ee4533ba213bf3ca2bdf5e9d16b02df92420b90dc439e07ef7433
+size 81827297

val2017.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49172589a65ac3760aff56027878d986fc3c7897fd5f7b8e81a527bbcf289f34
+size 80303732