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
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
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
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
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
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
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
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
teaser['user']['photos'][0]['url']) for teaser in teasers}
for rec in recs:
user = rec['user']
rec_id = user['_id']
print(f"{Fore.GREEN}Analyzing {user['name']} ({rec_id}) ...")
for rec_photo in user['photos']:
print(f"\t{Fore.BLUE}Image {rec_photo['url']}")
rec_img = get_image(rec_photo['url'])
for (tea_id, tea_img) in teaser_images.items():
print(
f"\t\t{Fore.BLACK}{Style.BRIGHT}Comparing with teaser {tea_id}")
if (compare(rec_img, tea_img)):
for i, rec_found_img in enumerate([get_image(pic['url']) for pic in user['photos']]):
cv2.imshow(f"Rec {i}", rescale(rec_found_img, 30))
cv2.imshow("Teaser", rescale(tea_img, 30))
action = cv2.waitKey(0)
cv2.destroyAllWindows()
if (action == KEY_LIKE or action == KEY_LIKE - 32):
like(rec_id)
if (action == KEY_PASS or action == KEY_PASS - 32):
dislike(rec_id)
if (action == KEY_SUPERLIKE or action == KEY_SUPERLIKE - 32):
superlike(rec_id)
print("\n")
# Deinit Colorama
deinit()
#!/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)