"""
A first DarSIA image
====================

The five-minute tour: read a photograph as a physical :class:`~darsia.Image`,
inspect it, overlay a metric grid, and cut out a region of interest -- either in
physical coordinates (metres) or by raw pixel index.
"""

import os

import darsia

IMAGES = os.path.join("..", "images")

# %%
# Read an image and attach physical dimensions. ``width`` and ``height`` are the
# real-world extent of the photograph in metres.

image = darsia.imread(os.path.join(IMAGES, "baseline.jpg"), width=2.8, height=1.5)
image.show("baseline")

# %%
# A copy with a 10 cm metric grid drawn on top.

grid_image = image.add_grid(dx=0.1, dy=0.1)
grid_image.show("with grid")

# %%
# Extract a region of interest given by two physical corner points.

roi = darsia.make_coordinate([[1.5, 0], [2.8, 0.7]])
roi_image = image.subregion(roi)
roi_image.show("region of interest (metres)")

# %%
# The same call also accepts a tuple of slices to cut a region by raw pixel
# index -- handy when you are reading coordinates straight off the axes.

pixel_roi = image.subregion((slice(200, 900), slice(1500, 2800)))
pixel_roi.show("region of interest (pixels)")

# %%
# The physical metadata and the raw array are both accessible.

print("metadata:", image.metadata())
print("array shape:", image.img.shape)