def test_visualization(self):
"""Print color spaces: Test that visualization tools add images to list"""
op = IptPrintColorSpaces()
op.apply_test_values_overrides(use_cases=("Visualization", ))
wrapper = BaseImageProcessor(
"./ipso_phen/ipapi/samples/images/arabido_small.jpg",
database=None,
)
wrapper.store_images = True
res = op.process_wrapper(wrapper=wrapper)
self.assertTrue(res, "Failed to process Simple white balance")
self.assertGreater(len(wrapper.image_list), 0,
"Visualizations must add images to list")
def main():
# Get the file
# ____________
# Set working folder
old_wd = os.getcwd()
abspath = os.path.abspath(__file__)
fld_name = os.path.dirname(abspath)
os.chdir(fld_name)
# Construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True, help="Path to the image")
ap.add_argument("-d", "--destination", required=False, help="Destination folder")
ap.add_argument("-p", "--print_images", required=False, help="Print images, y or n")
ap.add_argument("-m", "--print_mosaic", required=False, help="Print mosaic, y or n")
args = vars(ap.parse_args())
file_name = args["image"]
print_images = args.get("print_images", "n") == "y"
print_mosaic = args.get("print_mosaic", "n") == "y"
dst_folder = args.get("destination", "")
# Restore working folder
os.chdir(old_wd)
# Build wrapper
# _____________
wrapper = BaseImageProcessor(file_name)
wrapper.lock = True
wrapper.store_image(wrapper.current_image, "true_source_image")
if print_images or print_mosaic:
wrapper.store_images = True
if print_images:
wrapper.write_images = "plot"
if print_mosaic:
wrapper.write_mosaic = "plot"
# Fix exposure
# ____________________
wrapper.current_image = call_ipt(
ipt_id="IptLinearTransformation",
source=wrapper,
return_type="result",
method="gamma_target",
target_brightness=145,
text_overlay=1,
)
# Store image name for analysis
wrapper.store_image(wrapper.current_image, "exposure_fixed")
analysis_image = "exposure_fixed"
if print_mosaic:
wrapper.store_image(wrapper.current_image, "fixed_source")
# Build static ROIs
# _________________
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="check_exp_pot_top",
roi_type="other",
tool_target="IptExposureChecker",
left=394,
width=1317,
top=1990,
height=70,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="check_exp_pot_bottom",
roi_type="other",
tool_target="IptExposureChecker",
left=394,
width=1317,
top=2049,
height=320,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="check_exp_top",
roi_type="other",
tool_target="IptExposureChecker",
left=1583,
width=461,
height=90,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="open_pot_top",
roi_type="open",
left=500,
width=1100,
top=1940,
height=200,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="erode_pot_bottom",
roi_type="erode",
left=500,
width=1100,
top=2140,
height=240,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="keep_roi",
left=200,
width=1600,
height=2350,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="erode_top_right",
roi_type="erode",
left=1606,
width=279,
top=2,
height=376,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="open_left_leg",
roi_type="open",
left=527,
width=140,
top=2050,
height=381,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="open_right_leg",
roi_type="open",
left=1390,
width=140,
top=2050,
height=381,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="split_threshold_inside_bottom",
tool_target="IptSplittedRangeThreshold",
left=489,
width=1071,
top=2019,
height=427,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="split_threshold_inside_top_right",
tool_target="IptSplittedRangeThreshold",
left=1593,
width=453,
height=370,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="split_threshold_inside_right",
tool_target="IptSplittedRangeThreshold",
left=1920,
width=125,
top=351,
height=2088,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
# Pre process image (make segmentation easier)
# ____________________________________________
wrapper.current_image = call_ipt(
ipt_id="IptPartialPosterizer",
source=wrapper,
return_type="result",
blue_color="black",
post_blue_value=41,
)
wrapper.current_image = call_ipt(
ipt_id="IptExposureChecker",
source=wrapper,
return_type="result",
overexposed_limit=200,
over_color="black",
underexposed_limit=40,
under_color="black",
show_grey_zones=1,
grey_zone_limit=2,
grey_zone_color="black",
roi_names="check_exp_pot_top,check_exp_top",
)
wrapper.current_image = call_ipt(
ipt_id="IptExposureChecker",
source=wrapper,
return_type="result",
overexposed_limit=180,
over_color="black",
underexposed_limit=20,
under_color="black",
show_grey_zones=1,
grey_zone_limit=6,
grey_zone_color="black",
roi_names="check_exp_pot_bottom",
)
if print_mosaic:
wrapper.store_image(wrapper.current_image, "pre_processed_image")
# Build coarse masks
# __________________
mask_list = []
current_mask_ = call_ipt(
ipt_id="IptThreshold",
source=wrapper,
return_type="result",
channel="l",
min_t=15,
)
mask_list.append(current_mask_)
current_mask_ = call_ipt(
ipt_id="IptSplittedRangeThreshold",
source=wrapper,
return_type="result",
channel="b",
roi_names="split_threshold_inside_bottom,split_threshold_inside_top_right,split_threshold_inside_right",
min_inside_t=135,
min_outside_t=120,
kernel_size=4,
build_mosaic=1,
)
mask_list.append(current_mask_)
# Merge masks
func = getattr(wrapper, "multi_and", None)
if func:
wrapper.mask = func([mask for mask in mask_list if mask is not None])
wrapper.store_image(wrapper.mask, f"mask_multi_and")
if print_mosaic:
wrapper.store_image(wrapper.mask, "coarse_mask")
else:
wrapper.error_holder.add_error("Unable to merge coarse masks")
return
# ROIs to be applied after mask merging
# _____________________________________
handled_rois = ["keep", "delete", "erode", "dilate", "open", "close"]
rois_list = [
roi
for roi in wrapper.rois_list
if roi.tag in handled_rois and not (roi.target and roi.target != "none")
]
wrapper.mask = wrapper.apply_roi_list(
img=wrapper.mask, rois=rois_list, print_dbg=True
)
if print_mosaic:
wrapper.store_image(wrapper.mask, "mask_after_roi")
# Clean merged mask
# _________________
wrapper.mask = call_ipt(
ipt_id="IptKeepLinkedContours",
source=wrapper,
return_type="result",
tolerance_distance=50,
tolerance_area=500,
root_position="MIDDLE_CENTER",
)
if wrapper.mask is None:
return
if print_mosaic:
wrapper.store_image(wrapper.mask, "clean_mask")
# Check that the mask is where it belongs
# _______________________________________
mask = None
if print_images:
res = True
enforcers_list = wrapper.get_rois({"enforce"})
for i, enforcer in enumerate(enforcers_list):
mask = wrapper.mask.copy()
mask = wrapper.keep_roi(mask, enforcer)
partial_ok = np.count_nonzero(mask) > 0
res = partial_ok and res
if partial_ok:
roi_img = np.dstack((np.zeros_like(mask), mask, np.zeros_like(mask)))
else:
roi_img = np.dstack((np.zeros_like(mask), np.zeros_like(mask), mask))
background_img = cv2.bitwise_and(
wrapper.mask, wrapper.mask, mask=255 - mask
)
img = cv2.bitwise_or(
roi_img, np.dstack((background_img, background_img, background_img))
)
enforcer.draw_to(img, line_width=4)
wrapper.store_image(img, f"enforcer_{i}_{enforcer.name}")
if not res:
return
else:
enforcers_list = wrapper.get_rois({"enforce"})
for i, enforcer in enumerate(enforcers_list):
mask = wrapper.mask.copy()
mask = wrapper.keep_roi(mask, enforcer)
if np.count_nonzero(mask) == 0:
return
# Print selection as color on bw background
# ____________________________________________
id_objects, obj_hierarchy = ipc.get_contours_and_hierarchy(
mask=mask, retrieve_mode=cv2.RETR_TREE, method=cv2.CHAIN_APPROX_NONE
)
wrapper.object_composition(wrapper.current_image, id_objects, obj_hierarchy)
# Build mosaic
# ____________
if print_mosaic:
wrapper.store_mosaic = "result"
wrapper.mosaic_data = np.array(
[
["fixed_source", "pre_processed_image", "coarse_mask"],
[
"mask_after_roi",
"clean_mask",
wrapper.draw_image(
src_image=wrapper.current_image,
src_mask=wrapper.mask,
background="bw",
foreground="source",
bck_grd_luma=120,
contour_thickness=6,
hull_thickness=6,
width_thickness=6,
height_thickness=6,
centroid_width=20,
centroid_line_width=8,
),
],
]
)
wrapper.print_mosaic(padding=4)
print("Done.")
def main():
# Get the file
# ____________
# Set working folder
old_wd = os.getcwd()
abspath = os.path.abspath(__file__)
fld_name = os.path.dirname(abspath)
os.chdir(fld_name)
# Construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True, help="Path to the image")
ap.add_argument("-d",
"--destination",
required=False,
help="Destination folder")
ap.add_argument("-p",
"--print_images",
required=False,
help="Print images, y or n")
ap.add_argument("-m",
"--print_mosaic",
required=False,
help="Print mosaic, y or n")
args = vars(ap.parse_args())
file_name = args["image"]
print_images = args.get("print_images", "n") == "y"
print_mosaic = args.get("print_mosaic", "n") == "y"
dst_folder = args.get("destination", "")
# Restore working folder
os.chdir(old_wd)
# Build wrapper
# _____________
wrapper = BaseImageProcessor(file_name)
wrapper.lock = True
wrapper.store_image(wrapper.current_image, "true_source_image")
if print_images or print_mosaic:
wrapper.store_images = True
if print_images:
wrapper.write_images = "plot"
if print_mosaic:
wrapper.write_mosaic = "plot"
# Fix exposure
# ____________________
wrapper.current_image = call_ipt(
ipt_id="IptLinearTransformation",
source=wrapper,
return_type="result",
method="alpha_beta_target",
target_brightness=150,
)
# Store image name for analysis
wrapper.store_image(wrapper.current_image, "exposure_fixed")
analysis_image = "exposure_fixed"
if print_mosaic:
wrapper.store_image(wrapper.current_image, "fixed_source")
# Build static ROIs
# _________________
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="keep_roi",
left=100,
width=1885,
top=300,
height=1740,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="check_roi",
roi_type="enforce",
left=840,
width=400,
top=1640,
height=400,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_type="other",
left=100,
width=1885,
top=300,
height=1740,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="open_pot_top",
roi_type="open",
left=710,
width=660,
top=1990,
height=50,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
roi = call_ipt_func(
ipt_id="IptRoiManager",
source=wrapper,
function_name="generate_roi",
roi_name="safe_roi",
roi_type="safe",
left=230,
width=1550,
top=350,
height=1580,
)
if roi is not None:
wrapper.add_roi(new_roi=roi)
# Pre process image (make segmentation easier)
# ____________________________________________
wrapper.current_image = call_ipt(
ipt_id="IptExposureChecker",
source=wrapper,
return_type="result",
overexposed_limit=175,
over_color="blue_cabin",
underexposed_limit=35,
under_color="blue_cabin",
)
wrapper.current_image = call_ipt(
ipt_id="IptPartialPosterizer",
source=wrapper,
return_type="result",
blue_color="blue_cabin",
post_blue_value=45,
)
if print_mosaic:
wrapper.store_image(wrapper.current_image, "pre_processed_image")
# Build coarse masks
# __________________
mask_list = []
current_mask_ = call_ipt(ipt_id="IptThreshold",
source=wrapper,
return_type="result",
max_t=100)
mask_list.append(current_mask_)
current_mask_ = call_ipt(
ipt_id="IptThreshold",
source=wrapper,
return_type="result",
channel="b",
min_t=125,
)
mask_list.append(current_mask_)
# Merge masks
func = getattr(wrapper, "multi_and", None)
if func:
wrapper.mask = func([mask for mask in mask_list if mask is not None])
wrapper.store_image(wrapper.mask, f"mask_multi_and")
if print_mosaic:
wrapper.store_image(wrapper.mask, "coarse_mask")
else:
logger.error("Unable to merge coarse masks")
return
# ROIs to be applied after mask merging
# _____________________________________
handled_rois = ["keep", "delete", "erode", "dilate", "open", "close"]
rois_list = [
roi for roi in wrapper.rois_list if roi.tag in handled_rois
and not (roi.target and roi.target != "none")
]
wrapper.mask = wrapper.apply_roi_list(img=wrapper.mask,
rois=rois_list,
print_dbg=True)
if print_mosaic:
wrapper.store_image(wrapper.mask, "mask_after_roi")
# Clean merged mask
# _________________
wrapper.mask = call_ipt(
ipt_id="IptKeepLinkedContours",
source=wrapper,
return_type="result",
tolerance_distance=50,
tolerance_area=100,
)
if wrapper.mask is None:
return
if print_mosaic:
wrapper.store_image(wrapper.mask, "clean_mask")
# Check that the mask is where it belongs
# _______________________________________
if print_images:
res = True
enforcers_list = wrapper.get_rois({"enforce"})
for i, enforcer in enumerate(enforcers_list):
mask = wrapper.mask.copy()
mask = wrapper.keep_roi(mask, enforcer)
partial_ok = np.count_nonzero(mask) > 0
res = partial_ok and res
if partial_ok:
roi_img = np.dstack(
(np.zeros_like(mask), mask, np.zeros_like(mask)))
else:
roi_img = np.dstack(
(np.zeros_like(mask), np.zeros_like(mask), mask))
background_img = cv2.bitwise_and(wrapper.mask,
wrapper.mask,
mask=255 - mask)
img = cv2.bitwise_or(
roi_img,
np.dstack((background_img, background_img, background_img)))
enforcer.draw_to(img, line_width=4)
wrapper.store_image(img, f"enforcer_{i}_{enforcer.name}")
if not res:
return
else:
enforcers_list = wrapper.get_rois({"enforce"})
for i, enforcer in enumerate(enforcers_list):
mask = wrapper.mask.copy()
mask = wrapper.keep_roi(mask, enforcer)
if np.count_nonzero(mask) == 0:
return
# Extract features
# ________________
wrapper.current_image = wrapper.retrieve_stored_image("exposure_fixed")
wrapper.csv_data_holder = AbstractCsvWriter()
current_data = call_ipt(ipt_id="IptAnalyseObservation",
source=wrapper,
return_type="data")
if isinstance(current_data, dict):
wrapper.csv_data_holder.data_list.update(current_data)
else:
logger.error("Failed to add extracted data")
current_data = call_ipt(ipt_id="IptAnalyzeChlorophyll",
source=wrapper,
return_type="data")
if isinstance(current_data, dict):
wrapper.csv_data_holder.data_list.update(current_data)
else:
logger.error("Failed to add extracted data")
current_data = call_ipt(ipt_id="IptAnalyzeColor",
source=wrapper,
return_type="data")
if isinstance(current_data, dict):
wrapper.csv_data_holder.data_list.update(current_data)
else:
logger.error("Failed to add extracted data")
current_data = call_ipt(ipt_id="IptAnalyzeObject",
source=wrapper,
return_type="data")
if isinstance(current_data, dict):
wrapper.csv_data_holder.data_list.update(current_data)
else:
logger.error("Failed to add extracted data")
# Save CSV
if dst_folder and (len(wrapper.csv_data_holder.data_list) > 0):
with open(
os.path.join(dst_folder, "",
wrapper.file_handler.file_name_no_ext + ".csv"),
"w",
newline="",
) as csv_file_:
wr = csv.writer(csv_file_, quoting=csv.QUOTE_NONE)
wr.writerow(wrapper.csv_data_holder.header_to_list())
wr.writerow(wrapper.csv_data_holder.data_to_list())
# Build mosaic
# ____________
if print_mosaic:
wrapper.store_mosaic = "result"
wrapper.mosaic_data = np.array([
["fixed_source", "pre_processed_image", "coarse_mask"],
[
"mask_after_roi",
"clean_mask",
wrapper.draw_image(
src_image=wrapper.current_image,
src_mask=wrapper.mask,
background="bw",
foreground="source",
bck_grd_luma=120,
contour_thickness=6,
hull_thickness=6,
width_thickness=6,
height_thickness=6,
centroid_width=20,
centroid_line_width=8,
),
],
])
wrapper.print_mosaic(padding=4)
print("Done.")