Exemplo n.º 1
0
def render_example(model_id):

    # select the car as object
    obj = bpy.data.objects[model_id]
    obj.select = True

    # scale the DimsPlane to illustrate dimensions
    plane = bpy.data.objects['DimsPlane']
    plane.location = [0, 0, 0]

    roi = bounds(obj)
    dims = [
        roi.x.max - roi.x.min, roi.y.max - roi.y.min, roi.z.max - roi.z.min
    ]
    dims = dict(zip(['x', 'y', 'z'], dims))

    plane.scale.x = dims['x'] * 0.5
    plane.scale.y = dims['y'] * 0.5

    # save a rendered example
    example_file = model['example_file']
    if not op.exists(atcadillac(op.dirname(example_file))):
        os.makedirs(atcadillac(op.dirname(example_file)))
    logging.info('writing example to %s' % example_file)
    render_scene(atcadillac(example_file))
Exemplo n.º 2
0
def alias(img,amount): #cheating with a mask
	length, width = bounds(img)
	channel = channels(img)
	post = avail(img)
	mask = [[0,0,0],[255,255,255],[0,0,0],
			[255,255,255],[255,255,255],[255,255,255],
			[0,0,0],[255,255,255],[0,0,0]]
	result = find(img,mask,(3,3))
	return result
Exemplo n.º 3
0
def find(img, mask, dims):  # this isn't actually blobbing anything
    length, width = bounds(img)
    height, breadth = dims
    result = like(img)
    img = img.load()
    height = int(height / 2)
    breadth = int(breadth / 2)
    for l in range(height, length - height):
        for w in range(breadth, width - breadth):
            pixel = img[l, w]
    return result
Exemplo n.º 4
0
def find(img,mask,dims): # this isn't actually blobbing anything
	length, width = bounds(img)
	height, breadth = dims
	result = like(img)
	img = img.load()
	height = int(height / 2)
	breadth = int(breadth / 2)
	for l in range(height,length-height):
		for w in range(breadth,width-breadth):
			pixel = img[l,w]
	return result
Exemplo n.º 5
0
def edge(img):
    avails = avail(img)
    result = like(img).load()
    length, width = bounds(img)
    img = img.load()
    for a in range(0, len(avails)):
        av = avails[a]
        for x in range(0, length):
            for y in range(0, width):
                if av == img[x, y]:
                    result[x, y] == av
    return result
Exemplo n.º 6
0
def edge(img):
	avails = avail(img)
	result = like(img).load()
	length,width = bounds(img)
	img = img.load()
	for a in range(0,len(avails)):
		av = avails[a]
		for x in range(0,length):
			for y in range(0,width):
				if av == img[x,y]:
					result[x,y] == av
	return result
Exemplo n.º 7
0
def sharpen(img, amount):  # not actually sharpening
    result = like(img)
    length, width = bounds(img)
    img = img.load()
    result = result.load()
    for left in range(1, length - 1):
        for top in range(1, width - 1):
            pixel = [0, 0, 0, 0]
            for l in range(-1, 1):
                for w in range(-1, 1):
                    pixel[0] += img[left + l, top + w][0]
                    pixel[1] += img[left + l, top + w][1]
                    pixel[2] += img[left + l, top + w][2]
            result[left, top] = tuple(pixel)
    return result
Exemplo n.º 8
0
def sharpen(img,amount): #not actually sharpening
	result = like(img)
	length, width = bounds(img)
	img = img.load()
	result = result.load()
	for left in range(1,length-1):
		for top in range(1,width-1):
			pixel = [0,0,0,0]
			for l in range(-1,1):
				for w in range(-1, 1):
					pixel[0] += img[left+l,top+w][0]
					pixel[1] += img[left+l,top+w][1]
					pixel[2] += img[left+l,top+w][2]
			result[left,top] = tuple(pixel)
	return result
Exemplo n.º 9
0
def alias(img, amount):  # cheating with a mask
    length, width = bounds(img)
    channel = channels(img)
    post = avail(img)
    mask = [
        [0, 0, 0],
        [255, 255, 255],
        [0, 0, 0],
        [255, 255, 255],
        [255, 255, 255],
        [255, 255, 255],
        [0, 0, 0],
        [255, 255, 255],
        [0, 0, 0],
    ]
    result = find(img, mask, (3, 3))
    return result
Exemplo n.º 10
0
def get_dims(model_id):

    # select the car as object
    obj = bpy.data.objects[model_id]
    obj.select = True

    # scale the DimsPlane to illustrate dimensions
    #plane = bpy.data.objects['DimsPlane']
    #plane.location = [0, 0, 0]

    roi = bounds(obj)
    dims = [
        roi.x.max - roi.x.min, roi.y.max - roi.y.min, roi.z.max - roi.z.min
    ]
    dims = dict(zip(['x', 'y', 'z'], dims))

    x_wheels = get_x_wheels(obj)

    return {'dims': dims, 'x_wheels': x_wheels}
Exemplo n.º 11
0
def group(img):  # automatically
    length, width = bounds(img)
    result = like(img).load()
    img = img.load()
    color = [255, 255, 255, 255]
    tolerance = [2, 2, 2, 2]
    for inc in range(1, 127):  # this is really really slow / iterative
        for x in range(length):
            for y in range(width):
                matches = 0
                if abs(img[x, y][0] - color[0]) < tolerance:
                    matches += 1
                if abs(img[x, y][1] - color[1]) < tolerance:
                    matches += 1
                if abs(img[x, y][2] - color[2]) < tolerance:
                    matches += 1
                if matches > 3:
                    result[x, y] = tuple(color)
    return result
Exemplo n.º 12
0
def group(img):#automatically
	length, width = bounds(img)
	result = like(img).load()
	img = img.load()
	color = [255,255,255,255]
	tolerance = [2,2,2,2]
	for inc in range(1,127): # this is really really slow / iterative
		for x in range(length):
			for y in range(width):
				matches = 0
				if (abs(img[x,y][0] - color[0]) < tolerance):
					matches += 1
				if (abs(img[x,y][1] - color[1]) < tolerance):
					matches += 1
				if (abs(img[x,y][2] - color[2]) < tolerance):
					matches += 1
				if matches > 3:
					result[x,y] = tuple(color)
	return result
Exemplo n.º 13
0
#!/usr/bin/env python
from utils import (load, take, show, bgr, image, like, bounds,
channels, crop, scale, color, avail, colorPicker)
from proto import alias, sharpen, group, find, edge, center, distance
from PIL import Image

print "# fast stuff"
img = load('samples/abstract/colors.png')
#b = take()
show(img)
b, g, r = bgr(img)
img = image(b,b,b)
test = like(img)
bound = bounds(b)
channel = channels(b)
coord = (0,0,50,50)
closer = crop(img, coord)
bigger = scale(closer, 2.0)
eyedrop = color(img, 0, 30)
pallet = avail(img)
colorPicker(img,0,30)

print "# slow stuff"
res1 = alias(img, .3)
res2 = sharpen(img, .3)
blob1 = group(img)
mask = Image.new("RGB", (50, 10), "white")
blob3 = find(img,mask,(3,3))
coords1 = edge(img)
coords2 = center(blob1)
dist = distance(0,3)