def render_plot(img, poses, bboxes):
renderer = Renderer(vertices_path="./pose_references/vertices_trans.npy",
triangles_path="./pose_references/triangles.npy")
(w, h) = img.size
image_intrinsics = np.array([[w + h, 0, w // 2], [0, w + h, h // 2],
[0, 0, 1]])
trans_vertices = renderer.transform_vertices(img, poses)
img = renderer.render(img, trans_vertices, alpha=1)
# for bbox in bboxes:
# bbox = bbox.astype(np.uint8)
# print(bbox)
# img = cv2.rectangle(img, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (255,0,0), 2)
return img
class Scene:
def __init__(self, light_variability=(20,8), gridlines_on=None, gridlines_width=None, gridlines_spacing=None):
if gridlines_on or gridlines_width or gridlines_spacing:
assert not (gridlines_on is None\
or gridlines_width is None\
or gridlines_spacing is None),\
"All gridlines variables must be set if any are"
self.rend = Renderer()
self.shapes = []
self.grid_shapes = []
self.center = np.array((0, 140, 300))
self.light_variability = light_variability
self.background_prims = []
background_lower_bound = -1e3
background_upper_bound = 1e3
wall_bound = 1e3
self.background_prims.append(
Tri([(-wall_bound, 0, wall_bound),
(wall_bound, 0, wall_bound),
(-wall_bound, 0, -wall_bound)]))
self.background_prims.append(
Tri([(-wall_bound, 0, -wall_bound),
(wall_bound, 0, wall_bound),
(wall_bound, 0, -wall_bound)]))
self.background_prims.append(
Tri([(-wall_bound, -50, wall_bound),
(0, wall_bound, wall_bound),
(wall_bound, -50, wall_bound)]))
if gridlines_on:
for i in range(int((background_upper_bound - background_lower_bound) / (gridlines_width + gridlines_spacing))):
offset = i * (gridlines_width + gridlines_spacing)
self.grid_shapes.append(Tri([(background_lower_bound + offset, 0.01, background_lower_bound),
(background_lower_bound + offset, 0.01, background_upper_bound),
(background_lower_bound + gridlines_width + offset, 0.01, background_lower_bound)]))
self.grid_shapes.append(Tri([(background_lower_bound + offset, 0.01, background_upper_bound),
(background_lower_bound + gridlines_width + offset, 0.01, background_upper_bound),
(background_lower_bound + gridlines_width + offset, 0.01, background_lower_bound)]))
self.grid_shapes.append(Tri([(background_lower_bound, 0.01, background_lower_bound + gridlines_width + offset),
(background_upper_bound, 0.01, background_lower_bound + offset),
(background_lower_bound, 0.01, background_lower_bound + offset)]))
self.grid_shapes.append(Tri([(background_upper_bound, 0.01, background_lower_bound + offset),
(background_lower_bound, 0.01, background_lower_bound + gridlines_width + offset),
(background_upper_bound, 0.01, background_lower_bound + gridlines_width + offset)]))
self.default_light = np.array((400, 300, -800))
self.default_intensity = 1000000
self.camera = Cam((0, 140, 300), (128, 128))
def calc_center(self):
return mean([shape.center for shape in self.shapes])
def add_object(self, i=-1):
if i<0:
i = randint(0, 7)
shape = [Sphere(self.center, 0.5),
Tetrahedron(self.center),
Cuboid(self.center),
Cylinder(self.center, 50),
Pyramid(self.center),
Cone(self.center, 50),
Torus(self.center, 0.5, 50, 0.15),
HollowCuboid(self.center, 0.15)][i]
shape.scale(35)
self.shapes.append(shape)
def mutate_object(self, shape):
shape.scale(randint(25, 40))
self.__rotate_object(shape)
self.__translate_object(shape)
def mutate_all_objects(self):
for shape in self.shapes:
self.__scale_object(shape)
self.__rotate_object(shape)
self.__translate_object(shape)
def crossover(self, scene):
offspring = Scene()
offspring.shapes = self.shapes + scene.shapes
shuffle(offspring.shapes)
offspring.shapes = offspring.shapes[:len(offspring.shapes)//2]
return offspring
def mutate(self):
if randint(0,1) == 0:
self.add_object()
else:
shape = self.shapes[randint(0, len(self.shapes) - 1)]
mutation = [self.__scale_object, self.__translate_object, self.__rotate_object][randint(0,2)]
mutation(shape)
def new_light(self, theta = 60, phi=8):
d = norm(self.default_light - self.center)
x_trans = d * math.sin(math.radians(theta))
z_trans = d * math.cos(math.radians(theta))
y_trans = d * math.sin(math.radians(phi))
translation = np.array((x_trans, y_trans, -z_trans))
return Lit(self.center + translation, self.default_intensity)
def __scale_object(self, shape):
for i in range(3):
shape.scale(uniform(0.8, 1.2), axis=i)
def __translate_object(self, shape):
shape.translate((randint(-50, 50), 0, randint(-50, 50)))
def ground_mesh(self):
for shape in self.shapes:
lowest_y = shape.lowest_y()
shape.translate((0, -lowest_y, 0))
def __rotate_object(self, shape):
shape.rotate(randint(0, 359), randint(0, 359), randint(0, 359))
def refocus_camera(self):
self.camera.location = self.calc_center()
def render(self):
surface_prims = []
light = self.new_light(*self.light_variability)#Lit(self.default_light, self.default_intensity)#
for shape in self.shapes:
surface_prims += shape.render()
views = [self.camera.view_from(-30, 0, 200)]
res_x, res_y = self.camera.resolution
return self.rend.render(views, light, surface_prims, self.background_prims, res_x, res_y, self.grid_shapes, grid_color=(0.7,0.7,0.7))
plt.gca().invert_yaxis()
subplot_count += 1
# plot SMPL predicted verts
plt.subplot(1, 3, subplot_count)
plt.scatter(pred_vertices_smpl[:, 0], pred_vertices_smpl[:, 1], s=0.6)
plt.gca().set_aspect('equal', adjustable='box')
plt.gca().invert_yaxis()
subplot_count += 1
plt.savefig(outfile + "_verts_plot.png", bbox_inches='tight')
# plt.show()
# Render non-parametric shape
img_gcnn = renderer.render(pred_vertices,
mesh.faces.cpu().numpy(),
camera_t=camera_translation,
img=img,
use_bg=True,
body_color='pink')
# Render parametric shape
img_smpl = renderer.render(pred_vertices_smpl,
mesh.faces.cpu().numpy(),
camera_t=camera_translation,
img=img,
use_bg=True,
body_color='light_blue')
# Render side views
aroundy = cv2.Rodrigues(np.array([0, np.radians(90.), 0]))[0]
center = pred_vertices.mean(axis=0)
center_smpl = pred_vertices.mean(axis=0)
from utils.renderer import Renderer, Cam, Lit, Tri
import cv2
rend = Renderer()
sp = Sphere((0, 0, 0), 25)
shapes = sp.render()
cuboid = Cuboid((0, 0, -100))
cuboid.scale(25, axis=0)
cuboid.scale(50, axis=1)
cuboid.scale(75, axis=2)
cuboid.rotate(90, 90)
shapes.extend(cuboid.render())
tetrahedron = Tetrahedron((100, 0, 0))
tetrahedron.scale(25, axis=0)
tetrahedron.scale(50, axis=1)
tetrahedron.scale(20, axis=2)
tetrahedron.rotate(45, 180)
shapes.extend(tetrahedron.render())
background_prims = []
background_prims.append(Tri([(-1000.00,-40.00,1000.00), (1000.00,-40.00, 1000.00), (-1000.00,-40.00,-1000.00)]))
background_prims.append(Tri([(-1000.00,-40.00,-1000.00), (1000.00,-40.00, 1000.00), (1000.00,-40.00,-1000.00)]))
light = Lit((125,300,35),79000)
camera = [Cam((200,222,83),( -.5,-.7,-.5), (640,480))]
shadow, noshadow = rend.render(camera, light, shapes, background_prims)
cv2.imwrite("shadow.png", shadow)
cv2.imwrite("noshadow.png", noshadow)
# Preprocess input image and generate predictions
img, norm_img = process_image(args.img, args.bbox, args.openpose, input_res=cfg.INPUT_RES)
with torch.no_grad():
out_dict = model(norm_img.to(model.device))
pred_vertices = out_dict['pred_vertices']
pred_camera = out_dict['camera']
# Calculate camera parameters for rendering
camera_translation = torch.stack([pred_camera[:,1], pred_camera[:,2], 2*cfg.FOCAL_LENGTH/(cfg.INPUT_RES * pred_camera[:,0] +1e-9)],dim=-1)
camera_translation = camera_translation[0].cpu().numpy()
pred_vertices = pred_vertices[0].cpu().numpy()
img = img.permute(1,2,0).cpu().numpy()
# Render non-parametric shape
img_render = renderer.render(pred_vertices,
camera_t=camera_translation,
img=img, use_bg=True, body_color='pink')
# Render side views
aroundy = cv2.Rodrigues(np.array([0, np.radians(90.), 0]))[0]
center = pred_vertices.mean(axis=0)
center_smpl = pred_vertices.mean(axis=0)
rot_vertices = np.dot((pred_vertices - center), aroundy) + center
# Render non-parametric shape
img_render_side = renderer.render(rot_vertices,
camera_t=camera_translation,
img=np.ones_like(img), use_bg=True, body_color='pink')
# Render parametric shape
outfile = args.img.split('.')[0] if args.outfile is None else args.outfile