Updating the Readme

README.md

@@ -34,4 +34,54 @@ size_categories:
 - n<1K
 ---
 
-# tiutolo
+# Failures in 3D printing Dataset
+
+This is a small dataset of images from failures in 3D print
+
+## Structure
+
+The structure of the dataset is
+
+- **image_id:** Id of the image
+- **image:** Image instance in PIL format
+- **width:** Width of the image in pixels
+- **height:** Height of the image in pixels
+- **objects:** bounding boxes in the images
+  - **bbox:** coordinates of the bounding box. The coordinates are [x_center, y_center, bbox width, bbox height]
+  - **categories:** category of the bounding box. The categories are 0: error, 1: extrusor, 2: part and 3: spaghetti
+
+
+
+## Download the dataset
+
+'''
+from datasets import load_dataset
+
+dataset = load_dataset('Javiai/failures-3D-print')
+'''
+
+## Show the Bounding Boxes
+
+'''
+import numpy as np
+import os
+from PIL import Image, ImageDraw
+
+image = dataset["train"][0]["image"]
+annotations = dataset["train"][0]["objects"]
+draw = ImageDraw.Draw(image)
+
+categories = ['error','extrusor','part','spagheti']
+
+id2label = {index: x for index, x in enumerate(categories, start=0)}
+label2id = {v: k for k, v in id2label.items()}
+
+for i in range(len(annotations["categories"])):
+    box = annotations["bbox"][i]
+    class_idx = annotations["categories"][i]
+    x, y, w, h = tuple(box)
+    draw.rectangle((x - w/2, y - h/2, x + w/2, y + h/2), outline="red", width=1)
+    draw.text((x - w/2, y - h/2), id2label[class_idx], fill="white")
+
+image
+'''