def _process_forward_result(self, y_argmax, logit, target, tag,
extraction_vals, main_folder, save_results):
# hack for avoiding storing logits for frames, which are not evaluated
if "DO_NOT_STORE_LOGITS" in tag:
logit = None
tag = tag.replace("_DO_NOT_STORE_LOGITS", "")
if "__" in tag.split("/")[-2]:
sp = tag.split("/")
sp2 = sp[-2].split("__")
assert len(sp2) == 2
folder = main_folder + sp2[0] + "/" + sp2[1] + "/"
else:
folder = main_folder + tag.split("/")[-2] + "/"
out_fn = folder + tag.split("/")[-1].replace(".jpg", ".png").replace(
".bin", ".png")
tf.gfile.MakeDirs(folder)
# TODO: generalize for multiple classes
measures = compute_measures_for_binary_segmentation(y_argmax, target)
if save_results:
if self.adjustable_output_layer:
save_with_pascal_colormap(out_fn, y_argmax)
else:
y_scaled = (y_argmax * 255).astype("uint8")
imsave(out_fn, numpy.squeeze(y_scaled, axis=2))
print(out_fn)
if logit is not None:
if self.save_as_png:
out_fn_logits = out_fn.replace(".png", "_prob.png")
import cv2
cv2.imwrite(out_fn_logits,
(logit[..., 0] *
numpy.iinfo(numpy.uint16).max).astype("uint16"))
else:
out_fn_logits = out_fn.replace(".png", ".pickle")
pickle.dump(logit, open(out_fn_logits, "w"),
pickle.HIGHEST_PROTOCOL)
for e in extraction_vals:
assert e.shape[0] == 1 # batch size should be 1 here for now
for name, val in zip(self.extractions, extraction_vals):
val = val[0] # remove batch dimension
sp = out_fn.replace(".png", ".bin").split("/")
sp[-1] = name + "_" + sp[-1]
out_fn_extract = "/".join(sp)
print(out_fn_extract)
val.tofile(out_fn_extract)
return measures
def do_seq(model, seq):
pattern = BASE_DIR + model + "/valid/" + seq + "/*/"
out_folder = BASE_DIR + model + "_merged/valid/" + seq + "/"
mkdir_p(out_folder)
object_folders = sorted(glob.glob(pattern))
filenames = sorted(
map(os.path.basename, glob.glob(object_folders[0] + "/*.pickle")))
for fn in filenames:
posteriors = [
pickle.load(open(obj_folder + "/" + fn))
for obj_folder in object_folders
]
background = numpy.stack([x[..., 0] for x in posteriors],
axis=2).min(axis=2, keepdims=True)
rest = numpy.stack([x[..., 1] for x in posteriors], axis=2)
combined = numpy.concatenate([background, rest], axis=2)
result = combined.argmax(axis=2)
out_fn = out_folder + fn.replace(".pickle", ".png")
print(out_fn)
save_with_pascal_colormap(out_fn, result)