def main():
# make a tuple of strings - input file names
t_input_files = ("CW2003_H14_M57_S54_msCam1_frame0to99.tiff",
) # notice comma(!)
for s_fname in t_input_files:
print("Input file: %s" % s_fname)
# create a multi-part movie object
oc_movie = CMuPaMovieTiff(t_input_files)
print("\nMovie information:")
print(oc_movie.df_info)
print()
l_frames = []
i_frame_id = 0
# read first N frames
while (oc_movie.read_next_frame()):
print("%s" % oc_movie.get_frame_stat())
l_frames.append(oc_movie.na_frame)
i_frame_id += 1
# if i_frame_id >= 30: break
# show the frames
print("\nUsage: (p)revious frame, (n)ext frame, (q)uit.")
moshow("frames", l_frames)
def show_diff(s_in_fname, i_frame_1, i_frame_2):
oc_movie = CMuPaMovieTiff((s_in_fname,))
print("\nMovie information:")
print(oc_movie.df_info)
print()
i_frame_id = 0
b_frame_1_found = False
b_frame_2_found = False
while(oc_movie.read_next_frame()):
print("%s" % oc_movie.get_frame_stat())
if i_frame_id == i_frame_1:
na_frame_1 = oc_movie.na_frame.copy().astype(np.float32)
b_frame_1_found = True
if i_frame_id == i_frame_2:
na_frame_2 = oc_movie.na_frame.copy().astype(np.float32)
b_frame_2_found = True
if b_frame_1_found and b_frame_2_found: break
i_frame_id += 1
# show difference between the requested pair of frames
plt.imshow(na_frame_1 - na_frame_2)
plt.show()
def pre_filter_all_with_mocorr(s_in_fname, oc_rec_cfg):
oc_movie = CMuPaMovieTiff((s_in_fname,))
l_frames = []
i_frame_id = 0
oc_pw_ecc = None
oc_motion_field = None
i_median_flt_sz = int(oc_rec_cfg["median_blur"])
while(oc_movie.read_next_frame()):
# print("Frame number:", i_frame_id)
# pre-filter each frame locally (used for debugging)
# na_frame = pre_filter_single_frame(oc_movie.na_frame)
na_frame = cv.medianBlur(oc_movie.na_frame, i_median_flt_sz)
na_frame_to_register = cv.normalize(na_frame, None, alpha=0, beta=1, norm_type=cv.NORM_MINMAX, dtype=cv.CV_32F)
if oc_pw_ecc is None:
oc_pw_ecc = CPieceWiseECC(
na_frame.shape[0], # frame height!
na_frame.shape[1], # frame width!
na_frame.dtype,
oc_rec_cfg
)
oc_motion_field = CMotionFieldDrawer(
na_frame.shape[0], # frame height!
na_frame.shape[1], # frame width!
int(oc_rec_cfg["pw_ecc_nrow_tiles"]),
int(oc_rec_cfg["pw_ecc_ncol_tiles"]),
f_zoom_coef=10.0
)
oc_pw_ecc.process_frame(na_frame, b_verbose=True)
# normal way to register the frames
oc_pw_ecc.register_frame()
# you can register frames with background left untouched, for debugging
# oc_pw_ecc.register_frame(na_input=na_frame_to_register)
if i_frame_id < 3:
plt.subplot(221)
plt.imshow(oc_pw_ecc.d_REG['PW_REG_corr_coef'][-1])
plt.subplot(222)
plt.imshow(oc_pw_ecc.d_REG['PW_REG_warp_matrix'][-1])
plt.subplot(223)
plt.imshow(oc_pw_ecc.d_REG['PW_REG_inter_patch_dist'][-1])
plt.subplot(224)
oc_motion_field.process_frame(oc_pw_ecc.oc_twM)
plt.imshow(oc_motion_field.na_out)
plt.show()
# l_frames.append(oc_pw_ecc.na_out.copy())
# l_frames.append(oc_pw_ecc.na_out_reg.copy())
l_frames.append(np.hstack([na_frame_to_register, oc_pw_ecc.na_out_reg]))
i_frame_id += 1
# if i_frame_id >= 10: break
print(oc_pw_ecc.d_REG['PW_REG_not_converged'])
print(oc_pw_ecc.d_REG['PW_REG_high_jumps'])
moshow("frames", l_frames)
def test_stibord_real_data(s_in_fname):
oc_movie = CMuPaMovieTiff((s_in_fname, ))
oc_movie.read_next_frame()
na_frame = oc_movie.na_frame.astype(np.float32)
DVAR(na_frame)
oc_stibord_image = CStiBordFrame(na_frame, 8, 8, 16, cv.BORDER_REFLECT_101)
print(oc_stibord_image)
for ix, iy in np.ndindex(oc_stibord_image.shape):
# oc_stibord_image[ix, iy] = oc_stibord_image[ix, iy]
oc_stibord_image[ix, iy] = np.flipud(oc_stibord_image[ix, iy])
plt.figure(figsize=(8, 8)) # figure size (W,H) in inches
plt.subplot(221)
plt.imshow(na_frame)
plt.subplot(222)
plt.imshow(oc_stibord_image['inner'])
oc_stibord_image.stitch()
plt.subplot(223)
plt.imshow(oc_stibord_image['inner'])
plt.subplot(224)
plt.imshow(na_frame - oc_stibord_image['inner'])
plt.tight_layout()
plt.show()
sys.exit()
def plot_result(s_input_dir, s_input_ini_file, s_fname_prefix):
# s_roi_fluo_fname = os.path.join(s_input_dir, s_fname_prefix + "roi_fluo.tiff")
# oc_fluo_movie = CMuPaMovieTiff((s_roi_fluo_fname,))
# s_roi_mask_fname = os.path.join(s_input_dir, s_fname_prefix + "roi_mask.tiff")
# oc_mask_movie = CMuPaMovieTiff((s_roi_mask_fname,))
s_register_fname = os.path.join(s_input_dir,
s_fname_prefix + "register.tiff")
oc_register_movie = CMuPaMovieTiff((s_register_fname, ))
s_fluo_data_fname = os.path.join(s_input_dir, s_fname_prefix + "fluo.npy")
d_fluo_data = np.load(s_fluo_data_fname, allow_pickle=True).item()
for s_key in d_fluo_data.keys():
DVAR(d_fluo_data[s_key], s_var_name=s_key)
oc_iproj = None
i_frame_id = 0
while (oc_register_movie.read_next_frame()):
if i_frame_id % 100 == 0:
print("%s" % oc_register_movie.get_frame_stat())
if i_frame_id == 0:
oc_iproj = CROISpecificIntensityProjector(
oc_register_movie.na_frame.shape[0], # frame height
oc_register_movie.na_frame.shape[1], # frame width
d_fluo_data)
oc_iproj.process_frame(oc_register_movie.na_frame)
i_frame_id += 1
# if i_frame_id >= 30: break
oc_iproj.finalize_projection()
oc_cmap = plt.cm.jet.copy()
oc_cmap.set_bad(color='black')
_, ax = plt.subplots(nrows=1, ncols=3, figsize=(14, 5))
ax[0].imshow(oc_iproj.d_IPROJ['IPROJ_ROI_fluo_raw'], cmap=oc_cmap)
ax[1].imshow(oc_iproj.d_IPROJ['IPROJ_ROI_fluo_max'], cmap=oc_cmap)
ax[2].imshow(oc_iproj.d_IPROJ['IPROJ_ROI_fluo_norm'], cmap=oc_cmap)
ax[0].set_title("ROI fluo (raw)")
ax[1].set_title("ROI fluo (at dF/F peak)")
ax[2].set_title("ROI fluo (norm by peak)")
s_out_fname = os.path.join(s_input_dir,
s_fname_prefix + "IPROJ_ROI_fluo.png")
plt.savefig(s_out_fname, dpi=300, bbox_inches='tight')
plt.show()
def show_whole_input(s_in_fname):
# create a multi-part movie object
oc_movie = CMuPaMovieTiff((s_in_fname,))
print("\nMovie information:")
print(oc_movie.df_info)
print()
l_frames = []
# read first N frames
while(oc_movie.read_next_frame()):
print("%s" % oc_movie.get_frame_stat())
l_frames.append(oc_movie.na_frame)
# show the frames
print("\nUsage: (p)revious frame, (n)ext frame, (q)uit.")
moshow("frames", l_frames)
def pre_filter_all_frames(s_in_fname):
l_frames = []
i_frame_id = 0
i_niter = 3
i_median_blur_sz = 5
oc_filter = CFastGuidedFilter(3)
oc_strel_kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (7,7))
oc_movie = CMuPaMovieTiff((s_in_fname,))
while(oc_movie.read_next_frame()):
na_frame = cv.medianBlur(oc_movie.na_frame, i_median_blur_sz)
oc_filter.process_frame(cv.normalize(na_frame, None, alpha=0, beta=1, norm_type=cv.NORM_MINMAX, dtype=cv.CV_32F))
na_background = cv.morphologyEx(oc_filter.na_out, cv.MORPH_OPEN, oc_strel_kernel, iterations=i_niter)
na_signal = cv.normalize(oc_filter.na_out - na_background, None, alpha=0, beta=255, norm_type=cv.NORM_MINMAX, dtype=cv.CV_8U)
# l_frames.append(na_signal)
l_frames.append(np.hstack([
cv.normalize(na_frame, None, alpha=0, beta=1, norm_type=cv.NORM_MINMAX, dtype=cv.CV_32F),
cv.normalize(na_signal, None, alpha=0, beta=1, norm_type=cv.NORM_MINMAX, dtype=cv.CV_32F),
]))
if i_frame_id % 10 == 0: print(i_frame_id)
i_frame_id += 1
moshow("frames", l_frames)
def main():
"""
The input directory contain files named similar to following pattern:
downsampled-McHugh_Lab_181_614_S000001_L01_ch01.tif
downsampled-McHugh_Lab_181_614_S000001_L01_ch02.tif
downsampled-McHugh_Lab_181_614_S000001_L01_ch03.tif
downsampled-McHugh_Lab_181_614_S000001_L01_ch04.tif
downsampled-McHugh_Lab_181_614_S000002_L01_ch01.tif
downsampled-McHugh_Lab_181_614_S000002_L01_ch02.tif
downsampled-McHugh_Lab_181_614_S000002_L01_ch03.tif
downsampled-McHugh_Lab_181_614_S000002_L01_ch04.tif
downsampled-McHugh_Lab_181_614_S000003_L01_ch01.tif
downsampled-McHugh_Lab_181_614_S000003_L01_ch02.tif
downsampled-McHugh_Lab_181_614_S000003_L01_ch03.tif
downsampled-McHugh_Lab_181_614_S000003_L01_ch04.tif
and so on.
"""
s_input_dir = "D:\\data\\hongshen\\McHugh_lab_181_614_stitching\\downsampled"
s_wcard_in = "downsampled-McHugh_Lab_181_614_S000*_L01_ch03.tif"
s_fname_out = "downsampled-McHugh_Lab_181_614_L01_ch03.tif"
if not os.path.isdir(s_input_dir):
print("This script require presence of big size input files.")
print(
"Seems like you don't have these files stored at expected location."
)
print("If you REALLY need these files please contact me. Exiting...")
sys.exit(0)
print("Input directory:\t%s" % s_input_dir)
t_input_files = enum_video_files(s_input_dir, s_wcard_in, i_num_pos=2)
print("Found %d input file(s)." % len(t_input_files))
# create a multi-part movie object
oc_movie = CMuPaMovieTiff(t_input_files)
print("\nMovie information:")
print(oc_movie.df_info)
# create tiff writer object for output data storage
oc_tiff_writer = CSingleTiffWriter(s_fname_out, b_delete_existing=True)
# initial values of top, bottom, left and right borders for frame cropping
i_min_top = 0
i_max_bot = 0
i_min_lef = 0
i_max_rig = 0
# the frame counter
i_frame_id = 0
# Stage 1:
# read and process frames one by one until the end
# calculate global values of the i_min_top, i_max_bot, i_min_lef, i_max_rig
while (oc_movie.read_next_frame()):
print("%s" % oc_movie.get_frame_stat())
_, na_borders = get_contour_mask(oc_movie.na_frame)
i_top, i_bot, i_lef, i_rig = na_borders
if i_frame_id == 0:
i_min_top = oc_movie.na_frame.shape[0]
i_min_lef = oc_movie.na_frame.shape[1]
else:
i_min_top = min(i_min_top, i_top)
i_max_bot = max(i_max_bot, i_bot)
i_min_lef = min(i_min_lef, i_lef)
i_max_rig = max(i_max_rig, i_rig)
i_frame_id += 1
if i_frame_id >= len(t_input_files): break
# reset the oc_movie object's state and the frame counter
oc_movie = CMuPaMovieTiff(t_input_files)
i_frame_id = 0
# Stage 2:
# read and process frames one by one until the end
# crop each frame according to the i_min_top, i_max_bot, i_min_lef, i_max_rig
# calculated above and erase pixels that does not belong to the contour mask
while (oc_movie.read_next_frame()):
print("%s" % oc_movie.get_frame_stat())
na_mask_image, _ = get_contour_mask(oc_movie.na_frame)
oc_movie.na_frame[np.where(na_mask_image == 0)] = 0
# write new contour frame into tiff file
oc_tiff_writer.write_next_frame(oc_movie.na_frame[i_min_lef:i_max_rig,
i_min_top:i_max_bot])
i_frame_id += 1
if i_frame_id >= len(t_input_files): break
# always close all tiff writers after usage!
oc_tiff_writer.close()
def main():
# load local configuration file
oc_rec_cfg = configparser.ConfigParser()
oc_rec_cfg.read("CW2003_H14_M57_S54_msCam1_frame0to99.ini")
# make a tuple of strings - input file names
t_input_files = ("CW2003_H14_M57_S54_msCam1_frame0to99.tiff",
) # notice comma(!)
for s_fname in t_input_files:
print("Input file: %s" % s_fname)
# create a multi-part movie object
oc_movie = CMuPaMovieTiff(t_input_files)
print("\nMovie information:")
print(oc_movie.df_info)
print()
oc_pc1_wiper = None
oc_register = None
l_frames = []
i_frame_id = 0
# read the movie frame by frame, register frames, stack with raw frame and add into the l_frames
while (oc_movie.read_next_frame()):
print("%s" % oc_movie.get_frame_stat())
if i_frame_id == 0:
oc_pc1_wiper = CPrinCompWiper(
oc_movie.na_frame.shape[0], # frame height!
oc_movie.na_frame.shape[1] # frame width!
)
oc_register = CFrameRegECC(
oc_movie.na_frame.shape[0], # frame height!
oc_movie.na_frame.shape[1], # frame width!
oc_movie.na_frame.dtype,
oc_rec_cfg["frame_registration"])
oc_pc1_wiper.process_frame(oc_movie.na_frame)
oc_register.process_frame(oc_pc1_wiper.na_out)
oc_register.register_frame()
na_frame_before = cv2.normalize(oc_movie.na_frame,
None,
alpha=0,
beta=1,
norm_type=cv2.NORM_MINMAX,
dtype=cv2.CV_32F)
na_frame_after = cv2.normalize(oc_register.na_out_reg,
None,
alpha=0,
beta=1,
norm_type=cv2.NORM_MINMAX,
dtype=cv2.CV_32F)
l_frames.append(np.vstack([na_frame_before, na_frame_after]))
i_frame_id += 1
# if i_frame_id >= 30: break
# show the frames
print("\nUsage: (p)revious frame, (n)ext frame, (q)uit.")
moshow("frames", l_frames)