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@lizuoyue
lizuoyue committed Nov 5, 2018
1 parent 3915e28 commit c1d141c
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Showing 2 changed files with 67 additions and 63 deletions.
128 changes: 66 additions & 62 deletions road_path/Evaluate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,7 +92,7 @@ def savePNG(mat1, mat2, filename):
os.popen('mkdir %s' % test_path.replace('./', ''))

eval_files = glob.glob(config.PATH[city_name]['img-%s' % mode] + '/*')
eval_files.sort()
# eval_files.sort()
eval_files = [item for item in eval_files if not (item.endswith('Building.png') or item.endswith('Road.png'))]

result = []
Expand All @@ -101,7 +101,7 @@ def savePNG(mat1, mat2, filename):
with open('Eval_%s_%s_%s.out' % (city_name, backbone, mode), 'w') as f:
# Restore weights
saver.restore(sess, model_to_load[:-5])
for img_seq, img_file in enumerate(eval_files):
for img_seq, img_file in enumerate(eval_files[100: 120]):

t = time.time()
img_id = int(img_file.split('/')[-1].split('.')[0])
Expand All @@ -115,70 +115,74 @@ def savePNG(mat1, mat2, filename):
savePNG(img, pred_boundary[0, ..., 0] * 255, test_path + '/%d-1.png' % img_id)
savePNG(img, pred_vertices[0, ..., 0] * 255, test_path + '/%d-2.png' % img_id)

# map_b, map_v, all_terminal, val2idx = getAllTerminal(pred_boundary[0], pred_vertices[0])
# feature = np.concatenate([feature, map_b[np.newaxis, ..., np.newaxis], map_v[np.newaxis, ..., np.newaxis]], axis = -1)
map_b, map_v, vertices, edges = getVE(pred_boundary[0], pred_vertices[0])
result.append({
'image_id': img_id,
'vertices': vertices,
'edges': edges
})

if vis:
savePNG(img, map_b, test_path + '/%d-3.png' % img_id)
savePNG(img, map_v, test_path + '/%d-4.png' % img_id)

time_res.append(time.time() - t)

# t = time.time()
# indices = []
# multi_roads = []
# prob_res_li = []
# do_times = 0
# import random
# random.shuffle(all_terminal)
# while len(all_terminal) > 0:
# index = all_terminal[0][1]
# terminal_1, terminal_2 = all_terminal[0][2:4]
# pred_v_out_1, prob_res_1, rnn_prob_1 = sess.run(pred_path_res, feed_dict = {ff: feature, tt: terminal_1})
# pred_v_out_2, prob_res_2, rnn_prob_2 = sess.run(pred_path_res, feed_dict = {ff: feature, tt: terminal_2})
# if rnn_prob_1[0] >= rnn_prob_2[0]:
# indices.append(index)
# multi_roads.append(pred_v_out_1[0])
# prob_res_li.append(prob_res_1[0])
# else:
# indices.append((index[1], index[0]))
# multi_roads.append(pred_v_out_2[0])
# prob_res_li.append(prob_res_2[0])
# path, all_pairs = recoverSinglePath(multi_roads[-1], val2idx)
# all_terminal = [(item[1][0] in index or item[1][1] in index, item) for item in all_terminal[1:] if item[1] not in all_pairs]
# all_terminal.sort()
# all_terminal = [item[1] for item in all_terminal]
# do_times += 1
# if do_times == 0:
# time_res.append(0)
# else:
# time_res.append((time.time() - t) / do_times)

# paths, pathImgs = recoverMultiPath(img.shape[0: 2], multi_roads)
# paths[paths > 1e-3] = 1.0
#######################
# map_b, map_v, vertices, edges = getVE(pred_boundary[0], pred_vertices[0])
# result.append({
# 'image_id': img_id,
# 'vertices': vertices,
# 'edges': edges
# })

# if vis:
# savePNG(img, paths, test_path + '/%d-5.png' % img_id)
# if not os.path.exists(test_path + '/%d' % img_id):
# os.makedirs(test_path + '/%d' % img_id)
# for i, pathImg in enumerate(pathImgs):
# savePNG(img, pathImg, test_path + '/%d/%d-%d.png' % ((img_id,) + indices[i]))
# np.save(test_path + '/%d/%d-%d.npy' % ((img_id,) + indices[i]), prob_res_li[i])
# savePNG(img, map_b, test_path + '/%d-3.png' % img_id)
# savePNG(img, map_v, test_path + '/%d-4.png' % img_id)

# time_res.append(time.time() - t)
########################

t = time.time()

map_b, map_v, all_terminal, val2idx = getAllTerminal(pred_boundary[0], pred_vertices[0])
feature = np.concatenate([feature, map_b[np.newaxis, ..., np.newaxis], map_v[np.newaxis, ..., np.newaxis]], axis = -1)

indices = []
multi_roads = []
prob_res_li = []
do_times = 0
import random
random.shuffle(all_terminal)
while len(all_terminal) > 0:
index = all_terminal[0][1]
terminal_1, terminal_2 = all_terminal[0][2:4]
pred_v_out_1, prob_res_1, rnn_prob_1 = sess.run(pred_path_res, feed_dict = {ff: feature, tt: terminal_1})
pred_v_out_2, prob_res_2, rnn_prob_2 = sess.run(pred_path_res, feed_dict = {ff: feature, tt: terminal_2})
if rnn_prob_1[0] >= rnn_prob_2[0]:
indices.append(index)
multi_roads.append(pred_v_out_1[0])
prob_res_li.append(prob_res_1[0])
else:
indices.append((index[1], index[0]))
multi_roads.append(pred_v_out_2[0])
prob_res_li.append(prob_res_2[0])
path, all_pairs = recoverSinglePath(multi_roads[-1], val2idx)
all_terminal = [(item[1][0] in index or item[1][1] in index, item) for item in all_terminal[1:] if item[1] not in all_pairs]
all_terminal.sort()
all_terminal = [item[1] for item in all_terminal]
do_times += 1
if do_times == 0:
time_res.append(0)
else:
time_res.append((time.time() - t) / do_times)

paths, pathImgs = recoverMultiPath(img.shape[0: 2], multi_roads)
paths[paths > 1e-3] = 1.0

if vis:
savePNG(img, paths, test_path + '/%d-5.png' % img_id)
if not os.path.exists(test_path + '/%d' % img_id):
os.makedirs(test_path + '/%d' % img_id)
for i, pathImg in enumerate(pathImgs):
savePNG(img, pathImg, test_path + '/%d/%d-%d.png' % ((img_id,) + indices[i]))
np.save(test_path + '/%d/%d-%d.npy' % ((img_id,) + indices[i]), prob_res_li[i])

f.write('%d, %d, %.3lf\n' % tuple(time_res))
f.flush()

if img_seq % 100 == 0:
with open('predictions_%s_%s_%s.json' % (city_name, backbone, mode), 'w') as fp:
fp.write(json.dumps(result, cls = NumpyEncoder))
fp.close()
# if img_seq % 100 == 0:
# with open('predictions_%s_%s_%s.json' % (city_name, backbone, mode), 'w') as fp:
# fp.write(json.dumps(result, cls = NumpyEncoder))
# fp.close()

with open('predictions_%s_%s_%s.json' % (city_name, backbone, mode), 'w') as fp:
fp.write(json.dumps(result, cls = NumpyEncoder))
fp.close()
# with open('predictions_%s_%s_%s.json' % (city_name, backbone, mode), 'w') as fp:
# fp.write(json.dumps(result, cls = NumpyEncoder))
# fp.close()
2 changes: 1 addition & 1 deletion road_polygon/LookLoss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ def process(filename, n = 1000):

if __name__ == '__main__':
server = 'dalab'
net = 'resnet50'
net = 'vgg16'
city = 'roadtracer-dalabgpu'
# os.popen('scp %s:~/thesis/road_polygon/Loss_train_%s_%s.out ./LossTrain.out' % (server, net, city))
# os.popen('scp %s:~/thesis/road_polygon/Loss_valid_%s_%s.out ./LossValid.out' % (server, net, city))
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