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Rudimenary ImageMobject
This commit is contained in:
Grant Sanderson
50
camera.py
50
camera.py
@ -7,7 +7,7 @@ from colour import Color
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import aggdraw
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from helpers import *
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from mobject import PMobject, VMobject
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from mobject import PMobject, VMobject, ImageMobject
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class Camera(object):
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CONFIG = {
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@ -91,6 +91,10 @@ class Camera(object):
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mobject.points, mobject.rgbs,
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self.adjusted_thickness(mobject.stroke_width)
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)
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elif isinstance(mobject, ImageMobject):
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self.display_image_mobject(mobject)
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else:
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raise Exception("Unknown mobject type: " + type(mobject))
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#TODO, more? Call out if it's unknown?
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self.display_multiple_vectorized_mobjects(vmobjects)
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@ -184,6 +188,50 @@ class Camera(object):
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new_pa[indices] = rgbs
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self.pixel_array = new_pa.reshape((ph, pw, 3))
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def display_image_mobject(self, image_mobject):
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corner_coords = self.points_to_pixel_coords(image_mobject.points)
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ul_coords, ur_coords, dl_coords = corner_coords
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right_vect = ur_coords - ul_coords
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down_vect = dl_coords - ul_coords
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impa = image_mobject.pixel_array
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oh, ow = self.pixel_array.shape[:2] #Outer width and height
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ih, iw = impa.shape[:2] #inner with and height
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rgb_len = self.pixel_array.shape[2]
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# List of all coordinates of pixels, given as (x, y),
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# which matches the return type of points_to_pixel_coords,
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# even though np.array indexing naturally happens as (y, x)
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all_pixel_coords = np.zeros((oh*ow, 2), dtype = 'int')
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a = np.arange(oh*ow, dtype = 'int')
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all_pixel_coords[:,0] = a%ow
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all_pixel_coords[:,1] = a/ow
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recentered_coords = all_pixel_coords - ul_coords
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coord_norms = np.linalg.norm(recentered_coords, axis = 1)
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with np.errstate(divide='ignore'):
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ix_coords, iy_coords = [
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np.divide(
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dim*np.dot(recentered_coords, vect),
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np.dot(vect, vect),
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)
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for vect, dim in (right_vect, iw), (down_vect, ih)
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]
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to_change = reduce(op.and_, [
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ix_coords >= 0, ix_coords < iw,
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iy_coords >= 0, iy_coords < ih,
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])
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n_to_change = np.sum(to_change)
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inner_flat_coords = iw*iy_coords[to_change] + ix_coords[to_change]
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flat_impa = impa.reshape((iw*ih, rgb_len))
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target_rgbs = flat_impa[inner_flat_coords, :]
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flat_pa = self.pixel_array.reshape((ow*oh, rgb_len))
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flat_pa[to_change] = target_rgbs
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def align_points_to_camera(self, points):
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## This is where projection should live
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return points - self.space_center
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@ -59,11 +59,14 @@ BOTTOM = SPACE_HEIGHT*DOWN
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LEFT_SIDE = SPACE_WIDTH*LEFT
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RIGHT_SIDE = SPACE_WIDTH*RIGHT
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# Change this to point to where you want
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# animation files to output
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MOVIE_DIR = os.path.join(os.path.expanduser('~'), "Dropbox/3b1b_videos/animations/")
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###
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THIS_DIR = os.path.dirname(os.path.realpath(__file__))
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FILE_DIR = os.path.join(THIS_DIR, "files")
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IMAGE_DIR = os.path.join(FILE_DIR, "images")
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GIF_DIR = os.path.join(FILE_DIR, "gifs")
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MOVIE_DIR = os.path.join(FILE_DIR, "movies")
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STAGED_SCENES_DIR = os.path.join(FILE_DIR, "staged_scenes")
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TEX_DIR = os.path.join(FILE_DIR, "Tex")
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TEX_IMAGE_DIR = os.path.join(IMAGE_DIR, "Tex")
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@ -7,3 +7,4 @@ __all__ = [
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from mobject import Mobject, Group
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from point_cloud_mobject import Point, Mobject1D, Mobject2D, PMobject
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from vectorized_mobject import VMobject, VGroup
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from image_mobject import ImageMobject
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@ -8,95 +8,41 @@ from helpers import *
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from mobject import Mobject
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from point_cloud_mobject import PMobject
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class ImageMobject(PMobject):
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class ImageMobject(Mobject):
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"""
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Automatically filters out black pixels
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"""
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CONFIG = {
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"filter_color" : "black",
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"invert" : False,
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"use_cache" : True,
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"stroke_width" : 1,
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"scale_factorue": 1.0,
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"should_center" : True,
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# "use_cache" : True,
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"height": 2.0,
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}
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def __init__(self, image_file, **kwargs):
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digest_locals(self)
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Mobject.__init__(self, **kwargs)
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self.name = to_camel_case(
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os.path.split(image_file)[-1].split(".")[0]
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)
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path = get_full_image_path(image_file)
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self.generate_points_from_file(path)
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self.scale(self.scale_factorue)
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if self.should_center:
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self.center()
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def generate_points_from_file(self, path):
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if self.use_cache and self.read_in_cached_attrs(path):
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return
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image = Image.open(path).convert('RGB')
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if self.invert:
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image = invert_image(image)
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self.generate_points_from_image_array(np.array(image))
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self.cache_attrs(path)
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def get_cached_attr_files(self, path, attrs):
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#Hash should be unique to (path, invert) pair
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unique_hash = str(hash(path+str(self.invert)))
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return [
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os.path.join(IMAGE_MOBJECT_DIR, unique_hash)+"."+attr
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for attr in attrs
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]
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def read_in_cached_attrs(self, path,
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attrs = ("points", "rgbs"),
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dtype = "float64"):
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cached_attr_files = self.get_cached_attr_files(path, attrs)
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if all(map(os.path.exists, cached_attr_files)):
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for attr, cache_file in zip(attrs, cached_attr_files):
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arr = np.fromfile(cache_file, dtype = dtype)
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arr = arr.reshape(arr.size/self.dim, self.dim)
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setattr(self, attr, arr)
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return True
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return False
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def cache_attrs(self, path,
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attrs = ("points", "rgbs"),
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dtype = "float64"):
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cached_attr_files = self.get_cached_attr_files(path, attrs)
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for attr, cache_file in zip(attrs, cached_attr_files):
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getattr(self, attr).astype(dtype).tofile(cache_file)
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def generate_points_from_image_array(self, image_array):
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height, width = image_array.shape[:2]
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#Flatten array, and find indices where rgb is not filter_rgb
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array = image_array.reshape((height * width, 3))
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filter_rgb = np.array(Color(self.filter_color).get_rgb())
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filter_rgb = 255*filter_rgb.astype('uint8')
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bools = array == filter_rgb
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bools = bools[:,0]*bools[:,1]*bools[:,2]
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indices = np.arange(height * width, dtype = 'int')[~bools]
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rgbs = array[indices, :].astype('float') / 255.0
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points = np.zeros((indices.size, 3), dtype = 'float64')
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points[:,0] = indices%width - width/2
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points[:,1] = -indices/width + height/2
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height, width = map(float, (height, width))
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if height / width > float(DEFAULT_HEIGHT) / DEFAULT_WIDTH:
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points *= 2 * SPACE_HEIGHT / height
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def __init__(self, filename_or_array, **kwargs):
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if isinstance(filename_or_array, str):
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path = get_full_image_path(filename_or_array)
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image = Image.open(path).convert("RGB")
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self.pixel_array = np.array(image)
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else:
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points *= 2 * SPACE_WIDTH / width
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self.add_points(points, rgbs = rgbs)
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return self
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class MobjectFromPixelArray(ImageMobject):
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def __init__(self, image_array, **kwargs):
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self.pixel_array = np.array(filename_or_array)
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Mobject.__init__(self, **kwargs)
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self.generate_points_from_image_array(image_array)
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def init_points(self):
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#Corresponding corners of image are fixed to these
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#Three points
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self.points = np.array([
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UP+LEFT,
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UP+RIGHT,
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DOWN+LEFT,
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])
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self.center()
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self.scale_to_fit_height(self.height)
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h, w = self.pixel_array.shape[:2]
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self.stretch_to_fit_width(self.height*w/h)
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