feat: update script dataset and include data from coco

data/test.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4c3c88a478e8bc55fb239a623c8fea70e33e21384cec74b82e6fa0d62e9b945
+size 464

data/train.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5a353d1d88a5379b2f73f5a87443161f0c15f6ed7ab8f6c82f2c16bf598d6365
+size 810019672

watermarkdataset.py

@@ -1,8 +1,8 @@
 import os
-import torch
+from glob import glob
+from PIL import Image
 
 import datasets
-from pycocotools.coco import COCO
 
 _DESCRIPTION = """\
     Watermark Dataset
@@ -10,7 +10,7 @@ _DESCRIPTION = """\
 
 _VERSION = datasets.Version("1.0.0")
 
-_REPO = "data"# "https://huggingface.co/datasets/bastienp/visible-watermark-pita/raw/main/data"
+_REPO = "data"
 _URLS = {"train": f"{_REPO}/train.zip", "valid": f"{_REPO}/valid.zip"}
 
 _CATEGORIES = ["watermark"]
@@ -31,11 +31,53 @@ class WatermarkPita(datasets.GeneratorBasedBuilder):
                     }),
                 }
             ),
-    
+
             description=_DESCRIPTION,
         )
 
     def _split_generators(self, dl_manager):
-        return 
+        data_dir = dl_manager.download_and_extract(_URLS)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"split": "train", "data_dir": data_dir["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"split": "valid", "data_dir": data_dir["valid"]},
+            ),
+        ]
+
+
+    def _generate_examples(self, split, data_dir):
+        image_dir = os.path.join(data_dir, "images")
+        label_dir = os.path.join(data_dir, "labels")
+
+        image_paths = sorted(glob(image_dir + "/*/*.png"))
+        label_paths = sorted(glob(label_dir + "/*/*.txt"))
+
+        for idx, (image_path, label_path) in enumerate(zip(image_paths, label_paths)):
+            im = Image.open(image_path)
+            width, height = im.size
+
+            with open(label_path, "r") as f:
+                lines = f.readlines()
+
+            objects = []
+            for line in lines:
+                line = line.strip().split()
+
+                bbox_class = int(line[0])
+                bbox_top_left = int(float(line[1]) * width)
+                bbox_top_right = int(float(line[2]) * height)
+                bbox_bottom_left = int(float(line[3]) * width)
+                bbox_bottom_right = int(float(line[4]) * height)
+
+
+                objects.append({
+                    "label": bbox_class,
+                    "bbox": [bbox_top_left, bbox_top_right, bbox_bottom_left, bbox_bottom_right]
+                })
 
-    def _generate_examples(self, images, metadata_path):
+            yield idx, {"image": image_path, "objects": objects}