def render_data(render_image=True, render_annotation=True):
path = pathjoin(tempfile.gettempdir(), "render_" + str(time.time()))
render_result = {}
if render_image:
png_path = path + ".png"
with set_image_render(), withattr(render, "filepath", png_path):
print("Render image using:", render.engine)
bpy.ops.render.render(write_still=True)
render_result["image"] = imread(png_path)
os.remove(png_path)
if render_annotation:
exr_path = path + ".exr"
with set_inst_material(), set_annotation_render(), withattr(
render, "filepath", exr_path
):
print("Render annotation using:", render.engine)
bpy.ops.render.render(write_still=True)
render_result["exr"] = parser_exr(exr_path)
os.remove(exr_path)
result = ImageWithAnnotation(**render_result)
if "render_6dof_pose" and "Camera" in bpy.data.objects:
objs = [obj for obj in bpy.data.objects if "inst_id" in obj]
ycb_meta = get_6dof_pose(bpy.data.objects["Camera"], objs, inst=result["inst"])
result["ycb_meta"] = ycb_meta
return result
def render_image():
render = bpy.data.scenes[0].render
png_path = tempfile.NamedTemporaryFile().name + ".png"
with set_image_render(), withattr(render, "filepath", png_path):
bpy.ops.render.render(write_still=True)
image = imread(png_path)[..., :3]
os.remove(png_path)
return image
file = OpenEXR.InputFile(exr_path)
header = file.header()
h, w = header["displayWindow"].max.y + 1, header["displayWindow"].max.x + 1
exr = ExrDict()
for key in header["channels"]:
assert header["channels"][key].type.__str__() == "FLOAT"
exr[key] = np.fromstring(file.channel(key),
dtype=np.float32).reshape(h, w)
file.close()
return exr
def test_parser_exr(exr_path="../tmp_exrs/cycles.exr"):
return parser_exr(exr_path)
if __name__ == "__main__":
from boxx import show, imread
exr_path = "tmp_exr.exr"
exr_path = "../tmp_exrs/untitled.exr"
exr_path = "/tmp/blender/tmp.exr"
exr = parser_exr(exr_path)
inst = exr.get_inst()
png = imread(exr_path.replace(".exr", ".png"))[..., :3]
ann = ImageWithAnnotation(png, exr)
vis = ann.vis()
show - vis
def f(imgn):
imread(imgn)
def f(imgn):
return uint8(resize(imread(imgn), (
218,
178,
)))
celebA_path = os.path.expanduser('~/dataset/celeba')
dataset = pathjoin(celebA_path, 'eyeglasses_stgan_dataset')
st_gan_dataset = pathjoin(dataset, 'tf_st_gan_dataset')
psa = sorted(glob(pathjoin(dataset, 'trainA/*')))[0::2]
psb = sorted(glob(pathjoin(dataset, 'trainB/*')))[1::2]
lena = len(psa)
lenb = len(psb)
attribute = np.zeros((lena + lenb, 40), np.bool)
attribute[-lenb:, 15] = True
img = imread(psa[0])
shape = img.shape
makedirs(p / st_gan_dataset)
imgns = psa + psb
if shape[:2] != (
218,
178,
):
def f(imgn):
return uint8(resize(imread(imgn), (
218,
178,
)))
# cfg.MODEL.WEIGHT = "/home/dl/junk/output/single/model_final.pth"
# cfg.freeze()
if args.pth:
cfg.MODEL.WEIGHT = args.pth
# prepare object that handles inference plus adds predictions on top of image
coco_demo = COCODemo(
cfg,
confidence_threshold=args.confidence_threshold,
show_mask_heatmaps=False,
masks_per_dim=2,
min_image_size=args.min_image_size,
)
imgps = sorted(glob(pathjoin(args.dir, "*.jpg")))
loopLog = LogLoopTime(imgps)
for imgp in imgps[:]:
img = imread(imgp)
# composite = coco_demo.run_on_opencv_image(img[...,[2,1,0]])[...,[2,1,0]]
# show-composite
bboxList = coco_demo.getBboxList(img)
visBboxList(img,
bboxList,
imgp,
pltshow=not cloud,
thresh=args.confidence_threshold,
classNames=classNames)
execmd("google-chrome {}".format(imgp.replace('.jpg', '.pdf')))
loopLog(imgp)
m1 = np.append(m1, [[0, 0, 1]], 0)
if m2.shape != (3, 3):
m2 = np.append(m2, [[0, 0, 1]], 0)
return m1.dot(m2)[:2]
keys = set(notWearKeys).intersection(set(trainKeys))
keys = bpp.replicaSplitKeys(keys)
for ind, imgn in enumerate(keys):
trainAP = pathjoin(trainADir, imgn)
trainBP = pathjoin(trainBDir, imgn)
try:
imread(trainAP)
imread(trainBP)
continue
except:
pass
d = landmark.loc[imgn]
imgp = pathjoin(imgdir, d.image_id)
img = imread(imgp)
toPoints = (d.lefteye_x, d.lefteye_y), (d.righteye_x,
d.righteye_y), (d.nose_x, d.nose_y)
toPoints = (d.lefteye_x,
d.lefteye_y), (d.righteye_x,
d.righteye_y), (d.lefteye_x + d.righteye_y -
d.lefteye_y, d.lefteye_y +