import unittest
import numpy as np

from cvdatasets.dataset.part.base import BasePart

class PartCropTest(unittest.TestCase):


	def setUp(self):
		self.im = np.random.randn(300, 300, 3)

	def tearDown(self):
		pass

	def _check_crop(self, cropped_im, _should):

		self.assertIsNotNone(cropped_im,
			"method crop should return something!")

		self.assertIsInstance(cropped_im, type(self.im),
			"result should have the same type as the input image")

		crop_h, crop_w, _ = cropped_im.shape
		h, w, _ = _should.shape
		self.assertEqual(crop_h, h, "incorrect crop height")
		self.assertEqual(crop_w, w, "incorrect crop width")

		self.assertTrue((cropped_im == _should).all(),
			"crop was incorret")



	def test_bbox_part_crop(self):
		_id, x, y, w, h = annotation = (0, 20, 20, 100, 100)

		bbox = BasePart.new(self.im, annotation)

		cropped_im = bbox.crop(self.im)

		_should = self.im[y:y+h, x:x+w]
		self._check_crop(cropped_im, _should)

	def test_location_part_crop(self):
		_id, center_x, center_y, _vis = annotation = (0, 50, 50, 1)

		bbox = BasePart.new(self.im, annotation)

		h, w, c = self.im.shape
		for ratio in np.linspace(0.1, 0.3, num=9):
			_h, _w = int(h * ratio), int(w * ratio)
			cropped_im = bbox.crop(self.im, ratio=ratio)
			x, y = center_x - _h // 2, center_y - _w // 2
			_should = self.im[y : y + _h, x : x + _w]

			self._check_crop(cropped_im, _should)