def demo(width, height, angle_deg, orthogonal, pfm_output, png_output):
image = HdrImage(width, height)
# Create a world and populate it with a few shapes
world = World()
for x in [-0.5, 0.5]:
for y in [-0.5, 0.5]:
for z in [-0.5, 0.5]:
world.add(
Sphere(transformation=translation(Vec(x, y, z)) *
scaling(Vec(0.1, 0.1, 0.1))))
# Place two other balls in the bottom/left part of the cube, so
# that we can check if there are issues with the orientation of
# the image
world.add(
Sphere(transformation=translation(Vec(0.0, 0.0, -0.5)) *
scaling(Vec(0.1, 0.1, 0.1))))
world.add(
Sphere(transformation=translation(Vec(0.0, 0.5, 0.0)) *
scaling(Vec(0.1, 0.1, 0.1))))
# Initialize a camera
camera_tr = rotation_z(angle_deg=angle_deg) * translation(
Vec(-1.0, 0.0, 0.0))
if orthogonal:
camera = OrthogonalCamera(aspect_ratio=width / height,
transformation=camera_tr)
else:
camera = PerspectiveCamera(aspect_ratio=width / height,
transformation=camera_tr)
# Run the ray-tracer
tracer = ImageTracer(image=image, camera=camera)
def compute_color(ray: Ray) -> Color:
if world.ray_intersection(ray):
return WHITE
else:
return BLACK
tracer.fire_all_rays(compute_color)
# Save the HDR image
with open(pfm_output, "wb") as outf:
image.write_pfm(outf)
print(f"HDR demo image written to {pfm_output}")
# Apply tone-mapping to the image
image.normalize_image(factor=1.0)
image.clamp_image()
# Save the LDR image
with open(png_output, "wb") as outf:
image.write_ldr_image(outf, "PNG")
print(f"PNG demo image written to {png_output}")
def test_normalize_image(self):
img = HdrImage(2, 1)
img.set_pixel(0, 0, Color(0.5e1, 1.0e1, 1.5e1))
img.set_pixel(1, 0, Color(0.5e3, 1.0e3, 1.5e3))
img.normalize_image(factor=1000.0, luminosity=100.0)
assert img.get_pixel(0, 0).is_close(Color(0.5e2, 1.0e2, 1.5e2))
assert img.get_pixel(1, 0).is_close(Color(0.5e4, 1.0e4, 1.5e4))
def demo(width, height, algorithm, pfm_output, png_output, num_of_rays,
max_depth, init_state, init_seq, samples_per_pixel, declare_float,
input_scene_name):
samples_per_side = int(sqrt(samples_per_pixel))
if samples_per_side**2 != samples_per_pixel:
print(
f"Error, the number of samples per pixel ({samples_per_pixel}) must be a perfect square"
)
return
variables = build_variable_table(declare_float)
with open(input_scene_name, "rt") as f:
try:
scene = parse_scene(input_file=InputStream(
stream=f, file_name=input_scene_name),
variables=variables)
except GrammarError as e:
loc = e.location
print(f"{loc.file_name}:{loc.line_num}:{loc.col_num}: {e.message}")
sys.exit(1)
image = HdrImage(width, height)
print(f"Generating a {width}×{height} image")
# Run the ray-tracer
tracer = ImageTracer(image=image,
camera=scene.camera,
samples_per_side=samples_per_side)
if algorithm == "onoff":
print("Using on/off renderer")
renderer = OnOffRenderer(world=scene.world, background_color=BLACK)
elif algorithm == "flat":
print("Using flat renderer")
renderer = FlatRenderer(world=scene.world, background_color=BLACK)
elif algorithm == "pathtracing":
print("Using a path tracer")
renderer = PathTracer(
world=scene.world,
pcg=PCG(init_state=init_state, init_seq=init_seq),
num_of_rays=num_of_rays,
max_depth=max_depth,
)
elif algorithm == "pointlight":
print("Using a point-light tracer")
renderer = PointLightRenderer(world=scene.world,
background_color=BLACK)
else:
print(f"Unknown renderer: {algorithm}")
sys.exit(1)
def print_progress(row, col):
print(f"Rendering row {row + 1}/{image.height}\r", end="")
start_time = process_time()
tracer.fire_all_rays(renderer, callback=print_progress)
elapsed_time = process_time() - start_time
print(f"Rendering completed in {elapsed_time:.1f} s")
# Save the HDR image
with open(pfm_output, "wb") as outf:
image.write_pfm(outf)
print(f"HDR demo image written to {pfm_output}")
# Apply tone-mapping to the image
image.normalize_image(factor=1.0)
image.clamp_image()
# Save the LDR image
with open(png_output, "wb") as outf:
image.write_ldr_image(outf, "PNG")
print(f"PNG demo image written to {png_output}")