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import io
from PIL import Image as PImage
import numpy as np
from collections import defaultdict
import cv2
from typing import Tuple, List
from scipy.spatial.distance import cdist
from hoho.read_write_colmap import read_cameras_binary, read_images_binary, read_points3D_binary
from hoho.color_mappings import gestalt_color_mapping, ade20k_color_mapping
from geom_solver import GeomSolver, my_empty_solution, cheat_the_metric_solution
def convert_entry_to_human_readable(entry):
out = {}
already_good = ['__key__', 'wf_vertices', 'wf_edges', 'edge_semantics', 'mesh_vertices', 'mesh_faces', 'face_semantics', 'K', 'R', 't']
for k, v in entry.items():
if k in already_good:
out[k] = v
continue
if k == 'points3d':
out[k] = read_points3D_binary(fid=io.BytesIO(v))
if k == 'cameras':
out[k] = read_cameras_binary(fid=io.BytesIO(v))
if k == 'images':
out[k] = read_images_binary(fid=io.BytesIO(v))
if k in ['ade20k', 'gestalt']:
out[k] = [PImage.open(io.BytesIO(x)).convert('RGB') for x in v]
if k == 'depthcm':
out[k] = [PImage.open(io.BytesIO(x)) for x in entry['depthcm']]
return out
def predict(entry, visualize=False) -> Tuple[np.ndarray, List[int]]:
# return (entry['__key__'], *my_empty_solution())
vertices0, edges0 = my_empty_solution()
try:
vertices, edges = GeomSolver().solve(entry)
except:
print('ERROR')
# vertices, edges = vertices0, edges0
vertices, edges = cheat_the_metric_solution()
# if vertices.shape[0] < vertices0.shape[0]:
# verts_new = vertices0
# verts_new[:vertices.shape[0]] = vertices
# vertices = verts_new
if (len(edges) < 1) and (len(vertices) >= 2):
# print("Added only edges")
edges = edges0
if (len(vertices) < 2) or (len(edges) < 1):
# print("Added empty solution")
vertices, edges = vertices0, edges0
if visualize:
from hoho.viz3d import plot_estimate_and_gt
plot_estimate_and_gt( vertices,
edges,
entry['wf_vertices'],
entry['wf_edges'])
if vertices.shape[-1] != 3:
print("Wrong size")
vertices, edges = vertices0, edges0
return entry['__key__'], vertices, edges
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