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fix error in Issue https://github.com/j96w/DenseFusion/issues/127 #145

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fix error in Issue https://github.com/j96w/DenseFusion/issues/127 #145

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0037954
fix error in Issue https://github.com/j96w/DenseFusion/issues/127
bearpaw Mar 27, 2020
788a262
Fix knn import error. Issue https://github.com/j96w/DenseFusion/issue…
bearpaw Mar 27, 2020
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16 changes: 8 additions & 8 deletions datasets/linemod/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,14 +58,14 @@ def __init__(self, mode, num, add_noise, root, noise_trans, refine):
self.list_label.append('{0}/segnet_results/{1}_label/{2}_label.png'.format(self.root, '%02d' % item, input_line))
else:
self.list_label.append('{0}/data/{1}/mask/{2}.png'.format(self.root, '%02d' % item, input_line))

self.list_obj.append(item)
self.list_rank.append(int(input_line))

meta_file = open('{0}/data/{1}/gt.yml'.format(self.root, '%02d' % item), 'r')
self.meta[item] = yaml.load(meta_file)
self.pt[item] = ply_vtx('{0}/models/obj_{1}.ply'.format(self.root, '%02d' % item))

print("Object {0} buffer loaded".format(item))

self.length = len(self.list_rgb)
Expand All @@ -77,7 +77,7 @@ def __init__(self, mode, num, add_noise, root, noise_trans, refine):

self.xmap = np.array([[j for i in range(640)] for j in range(480)])
self.ymap = np.array([[i for i in range(640)] for j in range(480)])

self.num = num
self.add_noise = add_noise
self.trancolor = transforms.ColorJitter(0.2, 0.2, 0.2, 0.05)
Expand All @@ -93,7 +93,7 @@ def __getitem__(self, index):
depth = np.array(Image.open(self.list_depth[index]))
label = np.array(Image.open(self.list_label[index]))
obj = self.list_obj[index]
rank = self.list_rank[index]
rank = self.list_rank[index]

if obj == 2:
for i in range(0, len(self.meta[obj][rank])):
Expand All @@ -108,7 +108,7 @@ def __getitem__(self, index):
mask_label = ma.getmaskarray(ma.masked_equal(label, np.array(255)))
else:
mask_label = ma.getmaskarray(ma.masked_equal(label, np.array([255, 255, 255])))[:, :, 0]

mask = mask_label * mask_depth

if self.add_noise:
Expand Down Expand Up @@ -143,7 +143,7 @@ def __getitem__(self, index):
choose = choose[c_mask.nonzero()]
else:
choose = np.pad(choose, (0, self.num - len(choose)), 'wrap')

depth_masked = depth[rmin:rmax, cmin:cmax].flatten()[choose][:, np.newaxis].astype(np.float32)
xmap_masked = self.xmap[rmin:rmax, cmin:cmax].flatten()[choose][:, np.newaxis].astype(np.float32)
ymap_masked = self.ymap[rmin:rmax, cmin:cmax].flatten()[choose][:, np.newaxis].astype(np.float32)
Expand Down Expand Up @@ -215,7 +215,7 @@ def get_num_points_mesh(self):

def mask_to_bbox(mask):
mask = mask.astype(np.uint8)
_, contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
x = 0
y = 0
w = 0
Expand All @@ -239,7 +239,7 @@ def get_bbox(bbox):
if bbx[2] < 0:
bbx[2] = 0
if bbx[3] >= 640:
bbx[3] = 639
bbx[3] = 639
rmin, rmax, cmin, cmax = bbx[0], bbx[1], bbx[2], bbx[3]
r_b = rmax - rmin
for tt in range(len(border_list)):
Expand Down
2 changes: 1 addition & 1 deletion lib/knn/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
import functools
import torch
from torch.autograd import Variable, Function
from lib.knn import knn_pytorch as knn_pytorch
from lib.knn.knn_pytorch import knn_pytorch

class KNearestNeighbor(Function):
""" Compute k nearest neighbors for each query point.
Expand Down