Update README.md

README.md

@@ -32,7 +32,70 @@ task_categories:
 
 # MS-COCO2017
 
-Here is the code to build the dataset
+## Use the dataset
+
+```py
+from datasets import load_dataset
+ds = load_dataset("ariG23498/coco2017", streaming=True, split="validation")
+
+sample = next(iter(ds))
+
+from PIL import Image, ImageDraw
+
+def draw_bboxes_on_image(
+        image: Image.Image,
+        objects: dict,
+        category_names: dict = None,
+        box_color: str = "red",
+        text_color: str = "white"
+    ):
+    draw = ImageDraw.Draw(image)
+    bboxes = objects.get("bbox", [])
+    categories = objects.get("categories", [])
+
+    for i, bbox in enumerate(bboxes):
+        x, y, width, height = bbox
+        # PIL expects (x_min, y_min, x_max, y_max) for rectangle
+        x_min, y_min, x_max, y_max = x, y, x + width, y + height
+
+        # Draw the rectangle
+        draw.rectangle([x_min, y_min, x_max, y_max], outline=box_color, width=2)
+
+        # Get category label
+        category_id = categories[i]
+        label = str(category_id)
+        if category_names and category_id in category_names:
+            label = category_names[category_id]
+
+        # Draw the category label
+        text_bbox = draw.textbbox((x_min, y_min), label) # Use textbbox to get text size
+        text_width = text_bbox[2] - text_bbox[0]
+        text_height = text_bbox[3] - text_bbox[1]
+
+        # Draw a filled rectangle behind the text for better readability
+        draw.rectangle([x_min, y_min - text_height - 5, x_min + text_width + 5, y_min], fill=box_color)
+        draw.text((x_min + 2, y_min - text_height - 2), label, fill=text_color)
+
+    return image
+
+draw_bboxes_on_image(
+    image=sample["image"],
+    objects=sample["objects"],
+)
+```
+
+## Get the categories
+
+```py
+import json
+
+with open("/content/annotations/instances_train2017.json") as f:
+    instances = json.load(f)
+
+instances["categories"]
+```
+
+## Build the dataset and upload to Hub
 
 ```py
 !wget http://images.cocodataset.org/zips/train2017.zip
@@ -116,56 +179,4 @@ from datasets import load_dataset
 
 dataset = load_dataset("imagefolder", data_dir="/content/coco_imagefolder")
 dataset.push_to_hub("ariG23498/coco2017")
-```
-
-## Use the dataset
-
-```py
-from datasets import load_dataset
-ds = load_dataset("ariG23498/coco2017", streaming=True, split="validation")
-
-sample = next(iter(ds))
-
-from PIL import Image, ImageDraw
-
-def draw_bboxes_on_image(
-        image: Image.Image,
-        objects: dict,
-        category_names: dict = None,
-        box_color: str = "red",
-        text_color: str = "white"
-    ):
-    draw = ImageDraw.Draw(image)
-    bboxes = objects.get("bbox", [])
-    categories = objects.get("categories", [])
-
-    for i, bbox in enumerate(bboxes):
-        x, y, width, height = bbox
-        # PIL expects (x_min, y_min, x_max, y_max) for rectangle
-        x_min, y_min, x_max, y_max = x, y, x + width, y + height
-
-        # Draw the rectangle
-        draw.rectangle([x_min, y_min, x_max, y_max], outline=box_color, width=2)
-
-        # Get category label
-        category_id = categories[i]
-        label = str(category_id)
-        if category_names and category_id in category_names:
-            label = category_names[category_id]
-
-        # Draw the category label
-        text_bbox = draw.textbbox((x_min, y_min), label) # Use textbbox to get text size
-        text_width = text_bbox[2] - text_bbox[0]
-        text_height = text_bbox[3] - text_bbox[1]
-
-        # Draw a filled rectangle behind the text for better readability
-        draw.rectangle([x_min, y_min - text_height - 5, x_min + text_width + 5, y_min], fill=box_color)
-        draw.text((x_min + 2, y_min - text_height - 2), label, fill=text_color)
-
-    return image
-
-draw_bboxes_on_image(
-    image=sample["image"],
-    objects=sample["objects"],
-)
 ```