def load_transparent_test(self):
""" load_transparent_test:
Load an image with a known transparent channel.
"""
C = ph.load("tests/tree.png")
alpha = C.alpha.sum()
assert alpha.sum() > 0
def load_missing_file_test(self):
""" load_missing_file_test
Raise an exception if a file is missing
"""
C = ph.load("THIS_IS_A_MISSING_FILE.png")
alpha = C.alpha.sum()
assert alpha.sum() > 0
def _apply_eye_makeup(image, **kwargs):
# Load the image in, transform the coordinates to the shape of the canvas
if isinstance(image, str):
canvas = ph.load(image)
landmarks = face_finder(image)[0]
elif isinstance(image, ph.Canvas):
canvas = image
landmarks = face_finder(canvas.img[:, :, :3])[0]
else:
print(f"Unknown type {type(image)}")
transform(canvas, landmarks)
return eye_makeup(canvas, landmarks, **kwargs)
def direct_load_test(self):
""" direct_load_test:
Load an image without creating a canvas.
"""
C = ph.Canvas(bg="yellow")
C += ph.circle(color="g")
C2 = ph.Canvas()
with tempfile.NamedTemporaryFile(suffix=".png") as F:
C.save(F.name)
C2 = ph.load(F.name)
dist = C.img[:, :, :3] - C2.img[:, :, :3]
dist = dist.astype(float) / 255
assert_equal(dist.sum(), 0)
def person_ghost(f_image):
loc = C.shape[1] // 2, C.shape[0] // 2
for i in tqdm(range(20)):
C2 = C.copy()
C2 += ph.filters.gaussian_blur(0.1, 0.1)
pastebox(C, C2.img, ~mask, loc)
return C
f_image = "movies/000750.jpg"
F_IMAGE = sorted(glob.glob('movies/*.jpg'))
random.shuffle(F_IMAGE)
for f in tqdm(F_IMAGE):
f_final = os.path.join(save_dest, os.path.basename(f))
mask = load_mask(f)
if mask is None:
continue
C = ph.load(f)
C = person_ghost(f)
#C.show()
C.save(f_final)
print(f_final)
if flip_vertical:
img = cv2.flip(img, 0)
if rotate_angle:
img = imutils.rotate(img, rotate_angle)
return img
f_jpg = "data/source_images/tessa1.jpg"
landmarks = face_finder(f_jpg)[0]
compute_centroids(landmarks)
ph.load(f_jpg).resize(0.5).save("docs/images/tessa1_src.jpg")
C = ph.load(f_jpg)
org = C.copy()
eye, mask, full_mask = cutbox(C, landmarks["right_eye"], 50)
# Blow out the mask a bit
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
mask = cv2.dilate(mask, kernel, iterations=10)
minds_eye = landmarks["right_eye_centroid"] + landmarks["left_eye_centroid"]
minds_eye /= 2
minds_eye[1] -= 100
minds_eye = minds_eye.round().astype(int)
def test_canvas():
canvas = ph.load("tests/tessa1.jpg")
return canvas
plt.plot(df.frame_n, df[key])
plt.plot(
df.frame_n,
smooth(df[key], 10),
'k',
)
plt.show()
exit()
df = df.sort_values(key)[::-1]
c = ph.Canvas()
for frame_n, val in zip(df.frame_n[:20], df[key][:20]):
f_jpg = f'data/frames/single_movie/Die.Hard.1988.720p.BRRip.x264-x0r.mkv/{frame_n:08d}.jpg'
c = ph.load(f_jpg)
min_dim = min(c.img.shape[0], c.img.shape[1])
scale = 256 / min_dim
#c = c.resize(scale)
#c = c.resize(output_size=(256,256))
# Center crop
#remaining = max(c.img.shape[0], c.img.shape[1]) - 256
#c.img = c.img[:, remaining//2:remaining//2+256]
c += ph.text(f"frame:{frame_n}", font_size=0.25, y=-1.5)
c += ph.text(f"{key}:{val:0.3f}", font_size=0.25, y=1.5)
c.show(0)
mask = None
with h5py.File(f_h5) as h5:
for key in h5:
if h5[key].attrs['label'] != 'person':
continue
#if h5[key].attrs['label'] == 'person':
# continue
if mask is None:
mask = h5[key]['mask'][...]
else:
mask += h5[key]['mask'][...]
C = ph.load(f_image)
print(C.shape, C.img.shape)
def pastebox(canvas, img, fmask, location):
mask = np.zeros((*canvas.img.shape[:2], 3), canvas.img.dtype)
mask[fmask] = [255] * 3
#mask[:,:] = [255,255,255]
#canvas.img[fmask] = 0
#print(loc)
#print(canvas.shape)
#canvas.show()
#exit()
print(mask.shape, canvas.img.shape, img.shape)
import pixelhouse as ph
from greasepaint import eyeliner, eyeshadow
vaporwave_pal = ["#FF6AD5", "#C774E8", "#AD8CFF", "#8795E8", "#94D0FF"]
f_jpg = "data/source_images/tessa1.jpg"
def crop_eyes(canvas, f_save):
canvas = canvas.copy()
canvas.img = canvas.img[200:270, 122:340]
return canvas.save(f_save)
canvas = ph.load(f_jpg)
crop_eyes(canvas, "docs/images/eyes0.jpg")
canvas = eyeliner(canvas)
crop_eyes(canvas, "docs/images/eyes1.jpg").show()
canvas.resize(.5).save("docs/images/tessa1_liner.jpg")
for k, p in enumerate(vaporwave_pal):
canvas = eyeshadow(f_jpg, color=p)
crop_eyes(canvas, f"docs/images/eyes{k+2}.jpg")
import pixelhouse as ph
import numpy as np
import glob
F_FLOW = sorted(glob.glob("data/flows/*"))
F_IMG = sorted(glob.glob("data/frames/*"))
for f0, f1 in zip(F_IMG, F_FLOW):
flow = np.load(f1)
c0 = ph.load(f0).resize(output_size=(flow.shape[:2][::-1]))
#flow -= flow.min()
#flow/= flow.max()
flow += 3
flow /= 6
print(flow.min(), flow.max())
flow = np.clip(flow, 0, 1)
c1 = c0.blank()
c1.img[:, :, 0] = (flow[:, :, 0] * 255).astype(np.uint8)
c1.img[:, :, 2] = (flow[:, :, 1] * 255).astype(np.uint8)
c1 += ph.filters.gaussian_blur()
c1.show()
#c0.show()
"Long", # Good, but entropy can be higher >= 0.4
"Medium", # Good, multiple character interactions
"Medium Close-Up", # Good, character interactions
]
for key in cols:
dx = df[df[key] > 0.90]
dx = dx[dx["frame_entropy"] < entropy_vals[key]]
time = dx["Length (seconds)"].sum() / 60
print(f"{key} total minutes {time:0.2f}")
df = df[df["frame_entropy"] < entropy_vals[target_col]]
df = df[df[target_col] > 0.90]
for _, row in df.iterrows():
n = int(row["Scene Number"])
for k in range(1, 4):
print(k)
f_img = f"data/scene_change/{name}/Die.Hard.1988.720p.BRRip.x264-x0r-Scene-{n:04d}-{k:02d}.jpg"
assert os.path.exists(f_img)
c = ph.load(f_img)
ex = row["frame_entropy"]
c += ph.text(f"Entropy {ex:0.3f}", x=1.5, y=-1.5, font_size=0.25)
ex = row[target_col]
c += ph.text(f"{target_col} {ex:0.3f}", x=-1.5, y=-1.5, font_size=0.25)
c.show()