def reshape(width, height):
global camera, windowsize
glViewport(0, 0, width, height)
camera.projection = tr.perspective(50.0, width / float(height), 2.0, 10.0)
loc = glGetUniformLocation(program, "projectionMatrix")
glUniformMatrix4fv(loc, 1, GL_FALSE, camera.projection)
windowsize = (width, height)
def reshape(width, height):
gl.glViewport(0, 0, width, height)
projection = perspective(45.0, width / float(height), 2.0, 10.0)
program['u_projection'] = projection
def reshape(width,height):
global projection, view
gl.glViewport(0, 0, width, height)
projection = perspective( 45.0, width/float(height), 2.0, 10.0 )
view = np.identity(4,dtype=np.float32)
translate(view, 0,0,-5)
def reshape(width,height):
gl.glViewport(0, 0, width, height)
projection = perspective( 45.0, width/float(height), 2.0, 10.0 )
program['projection'] = projection
def on_reshape(width, height):
gl.glViewport(0, 0, width, height)
u_projection[...] = perspective( 25.0, width/float(height), 2.0, 10.0 )
def on_resize(self, width, height):
gl.glViewport(0, 0, width, height)
self.projection = perspective( 45.0, width/float(height), 2.0, 10.0 )
def on_resize(self, event):
width, height = event.size
gl.glViewport(0, 0, width, height)
self.projection = perspective(45.0, width / float(height), 2.0, 10.0)
self.program.uniforms['u_projection'] = self.projection
def on_resize(self, event):
width, height = event.size
gl.glViewport(0, 0, width, height)
self.projection = perspective( 45.0, width/float(height), 2.0, 10.0 )
self.program.uniforms['u_projection'] = self.projection
def on_reshape(width, height):
gl.glViewport(0, 0, width, height)
u_projection[...] = perspective(25.0, width / float(height), 2.0, 10.0)
def reshape(width,height):
global u_projection
gl.glViewport(0, 0, width, height)
u_projection = perspective( 25.0, width/float(height), 2.0, 10.0 )
def __call__(self, img):
"""Apply manipulations to image.
Args:
img (PIL Image): Image to be manipulated.
Returns:
PIL Image: Anchor Image (128x128)
PIL Image: Manipulated Image (128x128)
"""
cfg = self.config
anchor = transforms.center_crop(img, 128).copy()
# flipping
if np.random.rand() < cfg["p_horizontal_flip"]:
img = transforms.hflip(img)
if np.random.rand() < cfg["p_vertical_flip"]:
img = transforms.vflip(img)
# perspective
if "perspective_range" in cfg:
width, height = img.size
startpoints = np.array([(0, 0), (0, height), (width, height), (width, 0)])
rho = np.random.randint(*cfg["perspective_range"], startpoints.shape)
endpoints = startpoints + rho
img = transforms.perspective(img, startpoints, endpoints)
# affine
if "affine" in cfg:
scale = np.random.uniform(*cfg["affine"]["scale_range"])
rotation = np.random.uniform(*cfg["affine"]["rotation_range"])
translate = list(np.random.uniform(*cfg["affine"]["translation_range"], 2))
img = transforms.affine(img, rotation, translate, scale, shear=0)
# gamma
if "gamma_range" in cfg:
img = transforms.adjust_gamma(img, np.random.uniform(*cfg["gamma_range"]))
# hue
if "hue" in cfg:
img = transforms.adjust_hue(img, np.random.uniform(*cfg["hue_range"]))
# brightness
if "brightness_range" in cfg:
img = transforms.adjust_brightness(
img, np.random.uniform(*cfg["brightness_range"])
)
# contrast
if "contrast_range" in cfg:
img = transforms.adjust_contrast(
img, np.random.uniform(*cfg["contrast_range"])
)
if "p_global_hist" in cfg and np.random.rand() < cfg["p_global_hist"]:
img = (exposure.equalize_hist(np.array(img)) * 255).astype(np.uint8)
img = Image.fromarray(img)
elif "p_local_hist" in cfg and np.random.rand() < cfg["p_local_hist"]:
selem = disk(10)
img = (rank.equalize(np.array(img), selem=selem) * 255).astype(np.uint8)
img = Image.fromarray(img)
if np.random.rand() < cfg["p_invert"]:
img = ImageOps.invert(img)
if "p_blur" in cfg and np.random.rand() < cfg["p_blur"]:
img = img.filter(ImageFilter.GaussianBlur(radius=2))
if "p_jpeg" in cfg and np.random.rand() < cfg["p_jpeg"]:
buffer = io.BytesIO()
img.save(buffer, "JPEG", quality=50)
img = Image.open(buffer)
if "p_noise" in cfg and np.random.rand() < cfg["p_noise"]:
img = np.array(img)
img = img + np.random.normal(loc=0, scale=16, size=img.shape)
img = np.clip(img, 0, 255).astype(np.uint8)
img = Image.fromarray(img)
# grayscale
if "grayscale" in cfg:
img = transforms.to_grayscale(img, num_output_channels=cfg["grayscale"])
anchor = transforms.to_grayscale(
anchor, num_output_channels=cfg["grayscale"]
)
img = transforms.center_crop(img, 128)
return anchor, img
def on_resize(self, width, height):
gl.glViewport(0, 0, width, height)
self.projection = perspective(45.0, width / float(height), 2.0, 10.0)
