def analyze_centroid_displacement_history(files,
num_frames_per_iteration=1800):
"""
Given an array of file names,
get centroid displacement history iteratively over 30 mins of frames.
Args:
files ([type]): [description]
num_frames (int, optional): [description]. Defaults to 1800 (30 mins).
"""
total_frames = len(files)
analysis_results = {}
counter = 0
num_interval = 1
while counter < total_frames:
start_index = counter
if counter + num_frames_per_iteration > total_frames:
end_index = total_frames
else:
end_index = counter + num_frames_per_iteration
print("running analysis for {} - {}".format(
start_index, end_index))
startTime = basename(files[start_index])
endTime = basename(files[end_index])
displacement_dict = {
num_interval:
displacement_history(files[start_index:end_index], startTime,
endTime)
}
analysis_results = {**analysis_results, **displacement_dict}
counter += num_frames_per_iteration
num_interval += 1
return analysis_results
def test_frame_filter_for_movement_detection(with_godec=False, savegif=False):
noise_remover = FrameKalmanFilter()
save_path = kalman_pics_path + basename(data_path)
create_folder_if_absent(save_path)
data_i = get_frame_GREY(data[0])
subplt_titles = ["Original Image", "Movement", "KF Original"]
if with_godec:
subplt_titles.extend(["With Godec", "Movement", "KF Godec"])
ims = init_comparison_plot(data_i, subplt_titles, 2, 3)
M, LS, L, S, width, height = bs_godec(data)
noise_remover2 = FrameKalmanFilter()
elif not with_godec:
ims = init_comparison_plot(data_i, subplt_titles, 1, 3)
for i in tqdm(range(len(data))):
data_i = get_frame_GREY(data[i])
processed = noise_remover.process_frame(data_i)
movement = normalize_frame(processed - data_i)
imgs = [data_i, movement, processed]
if with_godec:
L_frame = normalize_frame(L[:, i].reshape(width, height).T)
S_frame = normalize_frame(S[:, i].reshape(width, height).T)
data_i2 = cleaned_godec_img(L_frame, S_frame)
processed2 = noise_remover2.process_frame(data_i2)
movement2 = normalize_frame(processed2 - data_i2)
imgs.extend([data_i2, movement2, processed2])
update_comparison_plot(ims, imgs)
plt.savefig(save_path + "/{}.png".format(i)) #make png
if savegif:
gif_pics = [save_path+ "/{}.png".format(i) for i in range(len(data))]
gif_path = kalman_gifs_path+basename(data_path)+"_movement.gif"
write_gif(gif_pics, gif_path, 0, len(gif_pics), fps=20)
optimize_size(gif_path)
def analyze_centroid_area_history(files,
num_frames_per_iteration=1800,
key_format="from_to"):
"""
Given an array of file names,
get centroid area history iteratively over 30 mins of frames.
Args:
files ([type]): [description]
num_frames (int, optional): [description]. Defaults to 1800 (30 mins).
"""
total_frames = len(files) # each frame is 1 second
analysis_results = {}
counter = 0
while counter < total_frames:
start_index = counter
if counter + num_frames_per_iteration > total_frames:
end_index = total_frames
else:
end_index = counter + num_frames_per_iteration
area_movement_counter = get_centroid_area_history(
files[start_index:end_index], debug=False, key_format="from_to")
dictkey = basename(files[start_index])
analysis_results[dictkey] = {
"keyformat": "from_to",
"duration": end_index - start_index,
"analysis": area_movement_counter
}
counter += num_frames_per_iteration
return analysis_results
def test_analyze_centroid_displacement_history():
data_path = "data/teck_one_day_activity"
files = get_all_files(data_path)
analysis_results = analyze_centroid_displacement_history(files)
print(analysis_results)
write_to_json(analysis_results,
"displacement_{}.json".format(basename(data_path)))
def test_frame_filter(savegif=False):
noise_remover = FrameKalmanFilter()
save_path = kalman_pics_path + basename(data_path)
create_folder_if_absent(save_path)
data_i = get_frame(data[0])
subplt_titles = ["Original Image", "noise removed"]
ims, axs, fig = init_noise_reduction_plot(data_i, subplt_titles)
for i in tqdm(range(len(data))):
data_i = get_frame(data[i])
processed = noise_remover.process_frame(data_i)
update_noise_reduction_plot(ims, [data_i, processed])
plt.savefig(save_path + "/{}.png".format(i)) #make png
if savegif:
gif_pics = [save_path+ "/{}.png".format(i) for i in range(len(data))]
gif_path = kalman_gifs_path+basename(data_path)+".gif"
write_gif(gif_pics, gif_path, 0, len(gif_pics), fps=30)
optimize_size(gif_path)
def test_analyze_centroid_area_history_short_time():
data_path = "data/teck_calib_2"
files = get_all_files(data_path)
analysis_results = analyze_centroid_area_history(files)
print(analysis_results)
write_to_json(
analysis_results, "sample_presence_detection_analysis/{}.json".format(
basename(data_path)))
def test_analyze_centroid_displacement_history():
start = time.time()
data_path = "data/dataset_for_xavier/2020.07.16"
files = get_all_files(data_path)
print("Number of files: {}".format(len(files)))
analysis_results = analyze_centroid_displacement_history(files)
json_name = basename(data_path)
print("Analysis done, writing to {}.json...".format(json_name))
write_to_json(analysis_results,
"displacement_history/{}.json".format(json_name))
end = time.time()
print("Time taken to collect displacement dictionary for {} files : {}".
format(len(files), end - start))
def test_bs_godec(files,
save_data=False,
save_gif=False,
gif_name=None,
fps=60):
"""Test bs_godec Implementation
Keyword Arguments:
save_data {bool} -- (default: {False})
save_gif {bool} -- (default: {False})
gif_name {string} -- (default: {None})
fps {int} -- (default: {60})
---
This test shows you different ways of running the bs_godec method and obtain the various type of data you need.
"""
print("Testing Godec...")
t = Timer("accumulate")
t.start()
M, LS, L, S, width, height = bs_godec(files)
print("M: ")
print(M)
print("L: ")
print(L)
t.stop("Time taken to run background subtraction with godec: ")
if save_data:
t.start()
npy_path = "godec_data/" + basename(data_path)
create_folder_if_absent(godec_data_path)
save_npy(M, npy_path, "M")
save_npy(L, npy_path, "L")
save_npy(S, npy_path, "S")
save_npy(LS, npy_path, "LS")
t.stop("Time taken to save godec result npy arrays: ")
plots_path = godec_pics_path + basename(data_path)
if not save_gif:
print("Plotting....")
t.start()
plot_godec(M,
LS,
L,
S,
plots_path,
width=width,
height=height,
preview=True)
t.stop("Time taken to save godec plots: ")
elif save_gif and gif_name:
print("Saving gif as {}....".format(gif_name))
t.start()
plot_godec(M, LS, L, S, plots_path, width=width, height=height)
pics = get_all_files(plots_path)
t.stop("Time taken to save godec plots: ")
write_gif(pics,
godec_gifs_path + gif_name,
start=0,
end=len(pics),
fps=fps)
print("The entire process has taken: ", t.timers['accumulate'], " seconds")