def test_region_mask(self):
mask = image_methods.get_region_masks(FITS_FILE, REG_FILE)[0]
imarray, header = image_methods.get_image_data(FITS_FILE)
mask = np.invert(mask)
imarray = mask * imarray
image_methods.show(imarray)
self.assertEqual(imarray[362, 75] == 0)
def test_detect_frcnn_long(self):
for im, name, labels, boxes in utils.tf_record_iterator(
f"{BASE_DIR}/frcnn_records/test/annotated.record"):
image_methods.show(im,
use_log=False,
annotations=zip(boxes, labels))
answer = image_methods.detect_comet(im, do_show=True)
def test_preprocess(self):
fig, ax = plt.subplots(1)
ax.imshow(IMARRAY, cmap="gray")
plt.show()
im = image_methods.median_filter_nans(IMARRAY)
im = image_methods.preprocess(im, resize=False)
im = image_methods.resize_image(im, 512)
image_methods.show(im, use_log=False)
def test_pyramid_propose(self):
image_methods.show(IMARRAY)
for sub_im, rect, ax in image_methods.pyramid_propose(
IMARRAY,
step=64,
zoom_step=1.5,
box_size=128,
orig_zoom=1,
do_show=True,
interactive=False):
time.sleep(.005)
def test_save_data(self):
save_file = COMET_PROCESSED_NP_IMAGES[:-4]
save_file_original = COMET_ORIG_NP_IMAGES[:-4]
ims = image_methods.get_normed_data(FITS_FOLDER, save_file,
save_file_original)
imarray = ims[0][10]
image_methods.show(imarray)
image_methods.get_normed_data(NOT_COMET_FITS_FOLDER,
file_for_orig=NOT_COMET_NP_IMAGES[:-4],
reg_files=False)
self.assertEqual(imarray, np.load(COMET_PROCESSED_NP_IMAGES)[0][10])
def test_untrained_comet_detection(self):
for images in utils.image_iterator(f"{BASE_DIR}/not_trained_comets"):
fits = images[0]
arrs = [image_methods.get_image_data(f)[0] for f in fits]
preprod = [
image_methods.preprocess(arr, resize=False) for arr in arrs
]
resized = [image_methods.resize_image(pre, 512) for pre in preprod]
comp = image_methods.get_composite_image(resized)
image_methods.show(comp)
answer = image_methods.detect_comet(preprod,
do_show=True,
im_type="composite")
print(answer)
def test_detect_3frcnn_long(self):
acc, count = (0, 0)
for im, name, labels, boxes in utils.tf_record_iterator(
f"{BASE_DIR}/data/band_3/c/test.record"):
print(name)
image_methods.show(im,
use_log=False,
annotations=zip(boxes, labels))
answer = image_methods.detect_comet(im,
do_show=True,
im_type="band_3")
acc += answer == ("comet" in labels)
count += 1
print(f"accuracy: {acc / count}")
def test_pipeline(self):
x = utils.image_iterator(FITS_FOLDER)
for _ in range(160):
scanfiles = next(x)
print(scanfiles[0])
ims = scanfiles[0]
ims = [image_methods.get_image_data(im)[0] for im in ims]
origs = ims.copy()
image_methods.show_many(np.array(origs))
preprod = [image_methods.preprocess(im, resize=False) for im in ims]
resized = [image_methods.resize_image(im, 512) for im in preprod]
image_methods.show_many(np.array(origs), row_2=np.array(resized))
composite = image_methods.get_composite_image(resized)
image_methods.show(composite, use_log=False)
image_methods.detect_comet(composite,
do_show=True,
im_type="composite")
def test_median_filter(self):
image_methods.show(IMARRAY)
IMARRAY = image_methods.median_filter_image(IMARRAY)
image_methods.show(IMARRAY)
def test_resize(self):
image_methods.show(IMARRAY)
IMARRAY = image_methods.resize_image(IMARRAY, 500)
image_methods.show(IMARRAY)
self.assertEqual(IMARRAY.shape[0], 500)
def test_get_data(self):
imarray, header = image_methods.get_image_data(FITS_FILE)
image_methods.show(imarray)
self.assertEqual(imarray[100, 100], 880.8705444335938)
self.assertEqual(header["RA0"], 304.529473280337)
def test_flip(self):
image_methods.show(IMARRAY)
flipped = image_methods.flip_image(IMARRAY, axis="y")
image_methods.show(flipped)
self.assertEqual(IMARRAY[0, 0], flipped[0, -1])
def test_rotate(self):
image_methods.show(IMARRAY)
rotated = image_methods.rotate_image(IMARRAY, 90)
image_methods.show(rotated)
self.assertEqual(IMARRAY[0, 0], rotated[-1, 0])