def test_get_depthmap():
saved_path = os.getcwd()
print(Image.__version__)
lon = -77.072465
lat = 38.985399
pano1 = GSV_pano(request_lon=lon,
request_lat=lat,
crs_local=6487,
saved_path=saved_path)
pano1.get_depthmap(zoom=0, saved_path=saved_path)
pano1.get_DOM(resolution=0.1)
def test_get_point_cloud(self):
panoId_2019 = "BM1Qt23drK3-yMWxYfOfVg"
panoId_2019 = "AZK1jDGIZC1zmuooSZCzEg" # Walker Ave to Franlin Elementary
# lat, lon = 40.7093514, -74.2453146 # road bridge ramp tilt, z = 37 m
# lat, lon = 40.780667, -73.9610365
pano1 = GSV_pano(panoId=panoId_2019, crs_local=6526)
# pano1 = GSV_pano(request_lon=lon, request_lat=lat, crs_local=6526, saved_path=os.getcwd())
dm = pano1.get_depthmap(zoom=0, saved_path=os.getcwd())
# point_cloud = pano1.get_point_cloud(distance_threshole=200, zoom=0)['point_cloud']
point_cloud = pano1.get_ground_points(color=True, zoom=4)
# point_cloud = pano1.get_DOM_points()
print(point_cloud.shape)
P = point_cloud
v = pptk.viewer(P[:, :3])
v.set(point_size=0.001, show_axis=False, show_grid=False)
# v.attributes(P[:, 4:7] / 255.0, P[:, 3], P[:, 8:11]/255.0, P[:, 7])
# v.attributes(P[:, 3:6] / 255.0) # for DOM points
v.attributes(P[:, 4:7] / 255.0)
def quick_DOM():
seg_dir = r'D:\DC_segmented'
pano_dir = r'E:\USC_OneDrive\OneDrive - University of South Carolina\Research\sidewalk_wheelchair\DC_panoramas'
seg_files = glob.glob(os.path.join(seg_dir, "*.png"))
pano_files = glob.glob(os.path.join(pano_dir, "*.jpg"))
saved_path = r'F:\Research\sidewalk_wheelchair\DOMs'
resolution = 0.05
img_w = 40
img_h = 40
zoom = 4
# pano_files.reverse()
# pano_files = pano_files[:]
for idx, pano_file in enumerate(pano_files[20000:]):
try:
print(f"Processing: {idx} / {len(pano_files)}, {pano_file}")
panoId = os.path.basename(pano_file)[:-6]
new_name = os.path.join(saved_path,
f"{panoId}_DOM_{resolution:0.2f}.tif")
if os.path.exists(new_name):
print(f"Skip processed panoramas: {panoId}")
continue
img_zoom = int(pano_file[-5])
if img_zoom == 4:
print("Skipe: ", pano_file)
continue
# if img_zoom == 5:
# img_zoom5 = Image.open(pano_file)
# pano_file = pano_file.replace("_5.jpg", "_4.jpg")
timer_start = time.perf_counter()
distance_threshole = img_w * 1.5
pano1 = GSV_pano(panoId=panoId,
saved_path=pano_dir,
crs_local=6487)
pano1.get_depthmap(zoom=zoom)
pano1.depthmap['ground_mask'] = np.where(
pano1.depthmap['depthMap'] < distance_threshole, 1, 0)
mask_h, mask_w = pano1.depthmap['ground_mask'].shape
pano1.depthmap['ground_mask'][int(mask_h / 4 * 3):, :] = 0
P = pano1.get_ground_points(zoom=zoom, color=True, img_type="pano")
# P = P[P[:, 3] < distance_threshole]
P = P[P[:, 0] < img_w / 2]
P = P[P[:, 0] > -img_w / 2]
P = P[P[:, 1] < img_h / 2]
P = P[P[:, 1] > -img_h / 2]
timer_end = time.perf_counter()
np_img, worldfile = pano1.points_to_DOM(P[:, 0],
P[:, 1],
P[:, 4:7],
resolution=resolution)
pano1.save_image(np_img, new_name, worldfile)
print("Time spent (second):", timer_end - timer_start)
except Exception as e:
print("Error in quick_DOM():", pano_file, e)