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)