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| """ Streamlit app """ | |
| import streamlit as st | |
| from openpiv import tools | |
| import imageio.v3 as iio | |
| import matplotlib.pyplot as plt | |
| from piv import simple_piv | |
| USER_GIF_URL = "https://github.com/alexlib/openpiv-app/raw/master/demo/ezgif.gif" | |
| urls = { | |
| "Birds 1": "https://64.media.tumblr.com/3decdb9824c82cc625396d5162b9c72c/tumblr_ohqkj1wMvh1qckzoqo2_500.gifv", | |
| "Birds 2": "https://64.media.tumblr.com/15d6395f97f2d12e32a764c4a17be406/699471e89e1d5634-11/s500x750/eabb9c7c1ea719d4b9889d8e0217a878ed3f7a3f.gifv", | |
| "PIV Standard Project": "http://www.vsj.jp/~pivstd/gif/image04.gif", | |
| "Sneezing": "https://www.npr.org/assets/img/2016/08/23/sneeze-slomo.gif", | |
| "Rankine vortex": "https://github.com/ElsevierSoftwareX/SOFTX_2020_33/raw/master/images/rankine_vortex07_0.gif", | |
| "Uniform+Vortex": "https://github.com/ElsevierSoftwareX/SOFTX_2020_33/raw/master/images/rk_uniform07_0.gif", | |
| "Stagnation flow": "https://github.com/ElsevierSoftwareX/SOFTX_2020_33/raw/master/images/stagnation07_0.gif", | |
| "Uniform flow": "https://github.com/ElsevierSoftwareX/SOFTX_2020_33/raw/master/images/uniform07_0.gif", | |
| "Parabolic profile": "https://github.com/ElsevierSoftwareX/SOFTX_2020_33/raw/master/images/parabolic07_0.gif", | |
| "Suction feeding fish": "https://i.makeagif.com/media/7-16-2015/7YeY1n.gif", | |
| "River (JPIV)": "https://eguvep.github.io/jpiv/fig/bode.gif", | |
| "User input": USER_GIF_URL, | |
| } | |
| st.sidebar.markdown("## Select GIF") | |
| # st.sidebar.markdown("You can **select** the values to change the *chart*.") | |
| # Using object notation | |
| with st.sidebar: | |
| choice = st.selectbox( | |
| "Select User input to paste your link:", | |
| urls.keys(), | |
| ) | |
| # # Using "with" notation | |
| # with st.sidebar: | |
| # add_radio = st.radio( | |
| # "Choose a shipping method", | |
| # ("Standard (5-15 days)", "Express (2-5 days)") | |
| # ) | |
| st.title("OpenPIV analysis of GIFs") | |
| st.markdown("## Selected:") | |
| st.write(choice) | |
| if choice == "User input": | |
| gifurl = st.text_input("Paster here a link to GIF file:", value=USER_GIF_URL) | |
| else: | |
| gifurl = urls[choice] | |
| # im = iio.imread(iio.core.urlopen(gifurl).read(), '.gif') | |
| # im = iio.get_reader(gifurl) | |
| im = iio.imread(gifurl, index=None) | |
| st.image(im[0]) | |
| images = [] | |
| for frame in im: | |
| # st.write(frame.shape) | |
| if frame.ndim > 2: | |
| frame = tools.rgb2gray(frame) | |
| images.append(frame) | |
| frame_range = st.slider( | |
| "Frames", value=(0, len(images)), min_value=0, max_value=len(images) | |
| ) | |
| # st.write(frame_range[0],frame_range[1]) | |
| window_size = st.select_slider("Select the window size", options=range(8, 256, 8), value=32) | |
| search_size = int(window_size * 2) | |
| overlap = int(window_size / 2) | |
| st.write("The window size is ", window_size) | |
| arrow_length = st.slider("Arrow length scaling", min_value=1, max_value=10, value=10) | |
| newgif = [] | |
| counter = frame_range[0] | |
| for I, J in zip( | |
| images[frame_range[0] : frame_range[1] - 1], | |
| images[frame_range[0] + 1 : frame_range[1]], | |
| ): | |
| x, y, u, v = simple_piv( | |
| I, | |
| J, | |
| window_size=window_size, | |
| search_size=search_size, | |
| overlap=overlap, | |
| plot=False) | |
| fig, ax = plt.subplots() | |
| ax.text(20, 20, str(counter), color="y") | |
| ax.imshow(I, cmap="gray", alpha=0.8, origin="upper") | |
| ax.quiver(x, y, u, -v, scale=10 * arrow_length, color="r") | |
| ax.axis("off") | |
| fig.savefig("tmp.png") | |
| # st.pyplot(fig) | |
| counter += 1 | |
| newgif.append(iio.imread("tmp.png")) | |
| iio.imwrite("tmp.gif", newgif) | |
| st.image("tmp.gif") | |
| # img_file_buffer = st.file_uploader("Upload a pair of images", type=["png", "jpg", "jpeg","tif","bmp"]) | |
| # img_file_extension = st.text("Extension") # need here to allow user to select image extension | |
| # window_size = st.slider( | |
| # "Interrogation Window Size", 8, 128, windef_settings.windowsizes[0], 8 | |
| # ) | |
| # confidence_threshold = st.slider( | |
| # "Confidence threshold", 0.0, 1.0, DEFAULT_CONFIDENCE_THRESHOLD, 0.05 | |
| # ) | |
| # confidence_threshold = st.slider( | |
| # "Confidence threshold", 0.0, 1.0, DEFAULT_CONFIDENCE_THRESHOLD, 0.05 | |
| # ) | |
| # confidence_threshold = st.slider( | |
| # "Confidence threshold", 0.0, 1.0, DEFAULT_CONFIDENCE_THRESHOLD, 0.05 | |
| # ) | |
| # if img_file_buffer is not None: | |
| # windef_settings.filepath_images = './demo' | |
| # windef_settings.frame_pattern_a = img_file_extension | |
| # windef_settings.frame_pattern_b = None | |
| # else: | |
| # # Format and Image Sequence | |
| # windef_settings.filepath_images = './demo' | |
| # windef_settings.frame_pattern_a = 'demo_b.bmp' | |
| # windef_settings.frame_pattern_b = 'demo_c.bmp' | |
| # # demo_image = DEMO_IMAGE | |
| # # image = np.array(Image.open(demo_image)) | |
| # success = process_images() | |
| # fig,ax = plot_result() | |
| # image, labels = annotate_image(image, detections, confidence_threshold) | |
| # st.image( | |
| # image, caption=f"Processed image", use_column_width=True, | |
| # ) | |
| # st.write(labels) | |
| # %% | |