def helper(image_path):
image = imread(image_path)
result, crop = p2v.reconstruct(image)
cropped_path = 'temp/cropped.jpg'
imwrite(cropped_path, crop)
landmarks = recognize_image(cropped_path, show_image=False)
return result['Z_surface'], landmarks, crop
def test_reconstruct(self):
image = imread('examples/sample.jpg')
results = p2v.reconstruct(image)
self.assertEqual(len(results), 2)
import pix2vertex as p2v from imageio import imread image_path = 'tommy-images/middle.jpg' image = imread(image_path) result, crop = p2v.reconstruct(image) # Interactive visualization in a notebook p2v.vis_depth_interactive(result['Z_surface']) # Static visualization using matplotlib p2v.vis_depth_matplotlib(crop, result['Z_surface']) # Export to STL p2v.save2stl(result['Z_surface'], 'res.stl')
'coords':
np.vstack([
grid.records().coords[:, 0],
grid.records().coords[:, 1],
nd_arr.ravel()
]).T
})
rec = GeoRecords(grid.proj, rec)
return rec
front = imread("front.jpeg")
left = imread("left.jpeg")
right = imread("right.jpeg")
result_front, crop_front = p2v.reconstruct(front)
result_left, crop_left = p2v.reconstruct(left)
result_right, crop_right = p2v.reconstruct(right)
front = result_front['Z_surface']
left = result_left['Z_surface']
right = result_right['Z_surface']
# Put NAN as 0
# front = front.copy()
# front[np.isnan(front)] = front[~np.isnan(front)].min()
# left = left.copy()
# left[np.isnan(left)] = left[~np.isnan(left)].min()
# right = right.copy()
# right[np.isnan(right)] = right[~np.isnan(right)].min()