Update README.md

README.md

@@ -795,6 +795,15 @@ Each instance has scalar attributes (canvas) and sequence attributes (elements).
   <PIL.PngImagePlugin.PngImageFile image mode=RGBA size=256x256>]}
 ```
 
+To get a label for categorical values, use the `int2str` method:
+
+```python
+key = "font"
+example = dataset[0]
+
+dataset.features[key].int2str(example[key])
+```
+
 ### Data Fields
 
 In the following, categorical fields are shown as `categorical` type, but the actual storage is `int64`.
@@ -851,6 +860,50 @@ The Crello dataset has 3 splits: train, validation, and test. The current split
 | test      | 2371  |
 
 
+### Visualization
+
+Each example can be visualized in the following approach. Note the following does not guarantee a similar appearance to the original template.
+
+```python
+def render(dataset: datasets.Dataset, example: Dict[str, Any], max_size: float=512.) -> bytes:
+    """Render parsed sequence example onto an image and return as PNG bytes."""
+    canvas_width = int(dataset.features["canvas_width"].int2str(example["canvas_width"]))
+    canvas_height = int(dataset.features["canvas_height"].int2str(example["canvas_height"]))
+
+    scale = min(1.0, max_size / canvas_width, max_size / canvas_height)
+
+    surface = skia.Surface(int(scale * canvas_width), int(scale * canvas_height))
+    with surface as canvas:
+        canvas.scale(scale, scale)
+        for index in range(example["length"]):
+            pil_image = example["image"][index]
+            image = skia.Image.frombytes(
+                pil_image.convert('RGBA').tobytes(),
+                pil_image.size,
+                skia.kRGBA_8888_ColorType)
+            left = example["left"][index] * canvas_width
+            top = example["top"][index] * canvas_height
+            width = example["width"][index] * canvas_width
+            height = example["height"][index] * canvas_height
+            rect = skia.Rect.MakeXYWH(left, top, width, height)
+
+            angle = example["angle"][index]
+            if angle != 0:
+                degree = 180. * angle / np.pi
+                canvas.save()
+                canvas.rotate(degree, left + width / 2., top + height / 2.)
+
+            canvas.drawImageRect(image, rect)
+            if angle != 0:
+                canvas.restore()
+
+    image = surface.makeImageSnapshot()
+    with io.BytesIO() as f:
+        image.save(f, skia.kPNG)
+        return f.getvalue()
+```
+
+
 ## Dataset Creation
 
 ### Curation Rationale