def process_detections(base_data_dir, detections):
# detections = list(detections)
# print('\n' + str(len(detections)) + '\n')
# sem.acquire()
imgpath = Path(base_data_dir) / Path(detections[0]['runguid']) / Path(
detections[0]['imagepath'], mode='r')
if not imgpath.exists():
print(imgpath)
return (None, None)
tiffimg = TIFF.open(str(imgpath))
img = Image.open(str(imgpath))
w = img.width
h = img.height
del img
image = np.empty((h, w, 4), dtype=np.uint8)
depth = np.empty((h, w), dtype=np.float32)
stencil = np.empty((h, w), dtype=np.uint8)
TIFF.setdirectory(tiffimg, 0)
TIFF.readencodedstrip(tiffimg, 0, image.ctypes.data, -1)
lastdir = num_directories(tiffimg) - 1
TIFF.setdirectory(tiffimg, lastdir - 1)
TIFF.readencodedstrip(tiffimg, 0, depth.ctypes.data, -1)
TIFF.setdirectory(tiffimg, lastdir)
TIFF.readencodedstrip(tiffimg, 0, stencil.ctypes.data, -1)
affines = [
create_affine(loads(x['rot']), loads(x['pos'])) for x in detections
]
bboxes_geom = [loads(x['fullbox']) for x in detections]
bboxes = [(np.array(loads(x['bbox3d_min'])),
np.array(loads(x['bbox3d_max']))) for x in detections]
handles = [x['handle'] for x in detections]
view = np.array(detections[0]['view_matrix'], dtype=np.float64)
proj = np.array(detections[0]['proj_matrix'], dtype=np.float64)
world_space = to_world_space(image, depth, proj, view, w, h)
output = np.zeros((h, w), dtype=np.uint32)
max = math.pow(2, 24) - 1
step = max // len(handles)
i = step
for box, xform, val in zip(bboxes, affines, handles):
output += paint_pixels(world_space, xform, box, val)
i += step
output_cars = stencil_cull(output, stencil, StenCode.car, w, h)
# output_peds = stencil_cull(output, stencil, StenCode.person, w, h)
# draw_bboxes(image, depth, proj, view, bboxes_geom, affines)
# colorout = cv2.applyColorMap(output.astype(np.uint8), cv2.COLORMAP_JET)
output_col = output_cars.view(np.uint8).reshape(output_cars.shape +
(4, ))[..., 1:4]
#cv2.imshow("color", output_col)
#cv2.waitKey(0)
result = get_bboxes(output_cars, detections, w, h)
# result += get_bboxes(output_peds, detections)
return (result, output_cars)
def get_img_from_directory(tiff_tmp, dir_num, dst_img):
TIFF.setdirectory(tiff_tmp, dir_num)
TIFF.readencodedstrip(tiff_tmp, 0, dst_img.ctypes.data, -1)
