.. meta::
   :description: Documentation of the coordinates system of the bounding boxes used in Konfuzio and some simple examples of how to use it for visualization, for example.

# Coordinates System

The size of a page of a document can be obtained in the document object.
The format is [width, height].

'original_size' corresponds to the size of the uploaded document (which can be a PDF file or an image).
  The bounding boxes of the annotations are based on this size.
   E.g.: original_size = [372.48, 463.68]

'size' is the dimension of the image representation of a document page. These representations are used for computer vision tasks and the SmartView.
  E.g.: size = [1552, 1932]


```python
from konfuzio_sdk.data import Project

my_project = Project(id_=YOUR_PROJECT_ID)
# first document uploaded
document = my_project.documents[0]
# index of the page to test
page_index = 0

original_size = document.pages[page_index]['original_size']
size = document.pages[page_index]['size']
```

The coordinates system used has its origin in the bottom left corner of the page.

![coordinates_system](../_static/img/coordinates_schema.png)


To visualize the character bounding boxes of a document and overlapping them in the image opened with the python
library PIL, for example, we can resize the image to the size in which they are based (original_size).
The following code can be used for this:

```python
import cv2
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from konfuzio_sdk.data import Project

my_project = Project(id_=YOUR_PROJECT_ID)
# first document uploaded
document = my_project.documents[0]
# index of the page to test
page_index = 0

doc_bbox = document.get_bbox()
document.get_images()
image_path = document.image_paths[page_index]

size = document.pages[page_index]['size']
original_size = document.pages[page_index]['original_size']

factor_x = original_size[0] / size[0]
factor_y = original_size[1] / size[1]

image = Image.open(image_path).convert('RGB')
image = image.resize((int(image.size[0] * factor_x), int(image.size[1] * factor_y)))
height = image.size[1]

image_characters_bbox = [char_bbox for _, char_bbox in doc_bbox.items() if char_bbox["page_number"] - 1 == page_index]

for bbox in image_characters_bbox:
    pp1 = (int(bbox["x0"]), int((height - bbox["y0"])))
    pp2 = (int(bbox["x1"]), int((height - bbox["y1"])))
    image = cv2.rectangle(np.array(image), pp1, pp2, (0, 255, 0), 1)

plt.imshow(image)
plt.show()

# Note: cv2 has the origin of the y coordinates in the upper left corner. Therefore, for visualization, the height of the
# image is subtracted to the y coordinates.
```

![characters_bboxes](../_static/img/bboxes_characters.png)

The coordinates obtained from the segmentation endpoint of the API are based on the image array shape.
To visualize the segmentation bounding boxes of a page on an image opened with the python library PIL, for example,
we can overlap them directly.

```python
import cv2
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from konfuzio_sdk.data import Project
from konfuzio_sdk.api import get_results_from_segmentation

my_project = Project(id_=YOUR_PROJECT_ID)
# first document uploaded
document = my_project.documents[0]
# index of the page to test
page_index = 0

document.get_images()
image_path = document.image_paths[page_index]
image = Image.open(image_path).convert('RGB')
image_segmentation_bboxes = get_results_from_segmentation(document.id_, my_project.id_)

for bbox in image_segmentation_bboxes[page_index]:
    pp1 = (int(bbox["x0"]), int(bbox["y0"]))
    pp2 = (int(bbox["x1"]), int(bbox["y1"]))
    image = cv2.rectangle(np.array(image), pp1, pp2, (255, 0, 0), 1)

plt.imshow(image)
plt.show()

```

![segmentation_bboxes](../_static/img/bboxes_segmentation.png)

To visualize both at the same time we can convert the coordinates from the segmentation result to be based on the image
size used for the characters' bbox.

```python
import cv2
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from konfuzio_sdk.data import Project
from konfuzio_sdk.api import get_results_from_segmentation

my_project = Project(id_=YOUR_PROJECT_ID)
# first document uploaded
document = my_project.documents[0]
# index of the page to test
page_index = 0

doc_bbox = document.get_bbox()
document.get_images()
image_path = document.image_paths[page_index]

original_size = document.pages[page_index]['original_size']
size = document.pages[page_index]['size']

factor_x = original_size[0] / size[0]
factor_y = original_size[1] / size[1]

image = Image.open(image_path).convert('RGB')
image_factor = image.copy()

image = image.resize((int(image.size[0] * factor_x), int(image.size[1] * factor_y)))
height = image.size[1]

image_characters_bbox = [char_bbox for _, char_bbox in doc_bbox.items() if char_bbox["page_number"] - 1 == page_index]

for bbox in image_characters_bbox:
    pp1 = (int(bbox["x0"]), int((height - bbox["y0"])))
    pp2 = (int(bbox["x1"]), int((height - bbox["y1"])))
    image = cv2.rectangle(np.array(image), pp1, pp2, (0, 255, 0), 1)

image_segmentation_bboxes = get_results_from_segmentation(document.id_, my_project.id_)

for bbox in image_segmentation_bboxes[page_index]:
    pp1 = (int(bbox["x0"] * factor_x), int(bbox["y0"] * factor_y))
    pp2 = (int(bbox["x1"] * factor_x), int(bbox["y1"] * factor_y))
    image = cv2.rectangle(np.array(image), pp1, pp2, (255, 0, 0), 1)

plt.imshow(image)
plt.show()
```
![characters_and_segmentation_bboxes](../_static/img/bboxes_overlap.png)