def extract_all_info(
self,
metadata,
background,
s,
act,
subact,
ca,
fno,
):
rotation_angle = None
im, joints_world, R, T, f, c = self.extract_info(
metadata, s, act, subact, ca, fno)
bbpx = bounding_box_pixel(joints_world, H36M_CONF.joints.root_idx, R,
T, f, c)
im, trans = self.crop_img(im, bbpx, rotation_angle)
background, _ = self.crop_img(background, bbpx, rotation_angle)
R_centre = cam_pointing_root(joints_world, H36M_CONF.joints.root_idx,
H36M_CONF.joints.number, R, T)
if rotation_angle is not None:
R_centre = np.dot(rotate_z(rotation_angle), R_centre)
R_pointing_centre = np.dot(R_centre, R)
#self.testing(joints_world, im, background, R, T, f, c, trans)
return im, R_pointing_centre, background, joints_world
def extract_image_info(self, s, act, subact, ca, fno, rotation_angle=None):
metadata = self.all_metadata[s][act][subact][ca]
im, joints_world, R, T, f, c= self.extract_info(metadata, s, act, subact, ca, fno)
bbpx = bounding_box_pixel(joints_world, H36M_CONF.joints.root_idx, R, T, f,c)
im, trans = self.crop_img(im, bbpx, rotation_angle)
R_centre = cam_pointing_root(joints_world, H36M_CONF.joints.root_idx, H36M_CONF.joints.number, R, T)
if rotation_angle is not None:
R_centre = np.dot(rotate_z(rotation_angle), R_centre)
R_pointing_centre = np.dot( R_centre, R)
return im, joints_world, R_pointing_centre
def extract_masks_info(self,s,act,subact,ca,fno, rotation_angle=None):
metadata = self.all_metadata[s][act][subact][ca]
im, joints_world, R, T, f, c = self.extract_mask_info(metadata, s, act, subact, ca, fno)
bbpx = bounding_box_pixel(joints_world, H36M_CONF.joints.root_idx, R, T, f, c)
im, trans = self.crop_img(im, bbpx, rotation_angle)
return im, R, T, f, c, trans
if __name__ == '__main__':
a = SMPL_Data_Load(2000,index_file_content=['s'],
index_file_list=[[6]],)
from utils.utils_H36M.visualise import Drawer
import matplotlib.pyplot as plt
d = Drawer()
im = a.load_image(6, 2, 2, 2, 371)
#im = np.transpose(im, axes=[1, 2, 0])
metadata = a.all_metadata[6][2][2][2]
im, joints_world, R, T, f, c = a.extract_info(metadata, 6, 2, 2, 2, 371)
bbpx = bounding_box_pixel(joints_world, H36M_CONF.joints.root_idx, R, T, f, c)
im, trans = a.crop_img(im, bbpx, None)
im2 = im.copy()
im2[:, :, 0] = im[:, :, 2]
im2[:, :, 2] = im[:, :, 0]
plt.axis('off')
plt.imshow(im2)
plt.title("ssksk")
plt.show()
#[6. 2. 1. 1. 101. 3.]
#[6. 2. 2. 1. 1. 4.]
#[6. 2. 2. 2. 371. 4.]
fig = plt.figure()
d.pose_3d(b['joints_im'], plot=True, fig=fig, azim=-90, elev=0)
plt.show()
from utils.utils_H36M.transformations import world_to_pixel, transform_2d_joints
joints_pix_torch = camera_to_pixels_batch(joints_cam_torch,17, f_torch, c_torch)
joint_px=world_to_pixel(
joints_world,
H36M_CONF.joints.number,
sample_metadata['R'],
sample_metadata['T'],
sample_metadata['f'],
sample_metadata['c']
)
bbpx_px=bounding_box_pixel(joints_world, 0, sample_metadata['R'], sample_metadata['T'], sample_metadata['f'], sample_metadata['c'])
imwarped,trans = get_patch_image(img, bbpx_px, (256,256), 0)#np.pi/4) # in degrees rotation around z axis
trans_torch = numpy_to_tensor_float(trans.reshape(1, 2, 3))
trsft_joints_torch = transform_2d_joints_batch(joints_pix_torch, trans_torch)
trsf_joints = transform_2d_joints(joint_px, trans)
trsft_joints_torch = tensor_to_numpy(trsft_joints_torch).reshape(17,2)
plt.figure()
imwarped=c.get_image(imwarped)
plt.imshow(imwarped)
plt.axis("off")
plt.show()