| import matplotlib.pyplot as plt |
| from matplotlib.patches import Polygon |
| from PDE2D.Coefficient import * |
| from PDE2D.utils import * |
| from PDE2D.BoundaryShape import * |
| from PDE2D.Solver import * |
| import matplotlib.gridspec as gridspec |
| import matplotlib.patches as patches |
| import matplotlib.animation as animation |
|
|
| def create_animation_shape(record, path, iternum, bbox, wos, wos_obj = None, resolution = [1024, 1024], type = "sdf", |
| plot_center = False): |
| |
| fig = plt.figure(figsize= (10, 5)) |
| g = gridspec.GridSpec(16, 32, figure = fig, wspace = 0.0, hspace=0.0) |
| ax1 = fig.add_subplot(g[:16, :16]) |
| ax2 = fig.add_subplot(g[:, 16:31]) |
| |
| if type == "sphere": |
| image_obj, ax_image, line = start_animation_sphere(ax1, ax2, record, bbox, wos, wos_obj, resolution, plot_center) |
| update = lambda iteration : update_sphere(iteration, record, resolution, line, ax_image, image_obj, bbox) |
| elif type == "sdf": |
| image_obj, ax_image, line = start_animation_sdf(ax1, ax2, record, bbox, wos, wos_obj, resolution, plot_center,) |
| update = lambda iteration : update_sdf(iteration, record, resolution, line, ax_image, image_obj, bbox) |
| |
| fig.subplots_adjust(left=0.01, bottom=0.05, right=0.97, top=0.95, wspace=0.01, hspace=0.05) |
|
|
| ani = animation.FuncAnimation(fig=fig, func=update, frames=iternum+1, interval=30) |
| writervideo = animation.FFMpegWriter(fps=25) |
| if wos_obj is not None: |
| ani.save(filename=f"{path}/reconstruction.gif", writer="pillow") |
| ani.save(f"{path}/reconstruction.mp4", writer=writervideo) |
| else: |
| ani.save(filename=f"{path}/reconstruction_wo_obj.gif", writer="pillow") |
| ani.save(f"{path}/reconstruction_wo_obj.mp4", writer=writervideo) |
| |
| def start_animation_sphere(ax1, ax2, record, bbox, wos, wos_obj = None, resolution = [1024, 1024], |
| plot_center = False): |
| ax1.set_axis_off() |
| image_obj = None |
| |
| wos.input.shape.sketch_image(ax1, bbox, resolution) |
| |
| if wos_obj is not None: |
| image_obj = wos_obj.input.shape.in_boundaries[0].sketch_image(ax1, bbox, resolution, channel = 0) |
| |
| radius_iter = record["inboundary.dirichlet.radius-0"] |
| origin_iter = record["inboundary.dirichlet.origin-0"] |
| circle = CircleShape(radius = radius_iter, origin = origin_iter) |
| |
| if image_obj is not None: |
| image_obj_ = np.array(image_obj) |
| else: |
| image_obj_ = None |
|
|
| image_iter = circle.sketch_image(ax1, bbox, resolution, image = image_obj_, channel = 2) |
| image_ax = ax1.imshow(image_iter) |
| if plot_center: |
| origin = point2sketch(wos.shape_holder.out_boundary.origin, bbox, resolution).numpy().squeeze() |
| ax1.scatter(origin[0], origin[1], color = "white", s = 0.5) |
| loss = record["loss"].sum(axis = 1) |
| iters = np.arange(0, len(loss)) |
| ax2.plot(iters, loss, color = "grey", ls = "-.") |
| line = ax2.plot(iters[0], loss[0], color = "red")[0] |
| ax2.set_yscale("log") |
| ax2.set_yscale("log") |
| ax2.grid() |
| |
|
|
| |
| ax1.set_title("Reconstruction") |
| ax2.set_title("Evolution of the Loss") |
| |
| return image_obj, image_ax, line |
| |
| def update_sphere(iteration, record, resolution, line, image_ax, image_obj, bbox): |
| radius_iter = record[f"inboundary.dirichlet.radius-{iteration}"] |
| origin_iter = record[f"inboundary.dirichlet.origin-{iteration}"] |
| circle = CircleShape(radius = radius_iter, origin = origin_iter) |
| fig, (ax_dummy) = plt.subplots(1, 1, figsize=[5, 5]) |
| if image_obj is not None: |
| image_obj_ = np.array(image_obj) |
| else: |
| image_obj_ = None |
| image_i = circle.sketch_image(ax_dummy, bbox, resolution, image = image_obj_, channel = 2) |
| plt.close(fig) |
| loss = record["loss"].sum(axis = 1)[:iteration] |
| iters = np.arange(0, iteration) |
| line.set_xdata(iters) |
| line.set_ydata(loss) |
| image_ax.set_data(image_i) |
|
|
|
|
| def start_animation_sdf(ax1, ax2, record, bbox, wos, wos_obj, resolution = [1024, 1024], plot_center = False, |
| center_bg = 1, deviate_bg = 0.02): |
| ax1.set_axis_off() |
| image_obj = None |
| |
| wos.input.shape.sketch_image(ax1, bbox, resolution) |
| |
| if wos_obj is not None: |
| image_obj = wos_obj.input.shape.in_boundaries[0].sketch_image(ax1, bbox, resolution, channel = 0) |
| |
| image_iter = record["inboundary.dirichlet.tensor-0"].squeeze() |
| box_length = bbox[1][0] - bbox[0][0] |
| box_center = [(bbox[0][0] + bbox[1][0])/2, (bbox[0][1] + bbox[1][1])/2] |
| sdf = SDFGrid(image_iter, box_length=box_length, box_center = box_center) |
| if image_obj is not None: |
| image_obj_ = np.array(image_obj) |
| else: |
| image_obj_ = None |
| image_iter = sdf.sketch_image(ax1, bbox, resolution, image = image_obj_, channel = 2) |
| image_ax = ax1.imshow(image_iter * 0.8) |
| if plot_center: |
| origin = point2sketch(wos.shape_holder.out_boundary.origin, bbox, resolution).numpy().squeeze() |
| ax1.scatter(origin[0], origin[1], color = "white", s = 0.3) |
|
|
| loss = record["loss"].sum(axis = 1) |
| iters = np.arange(0, len(loss)) |
| ax2.plot(iters, loss, color = "grey", ls = "-.") |
| line = ax2.plot(iters[0], loss[0], color = "red")[0] |
| ax2.set_yscale("log") |
| ax2.set_yscale("log") |
| ax2.grid() |
|
|
| |
| ax1.set_title("Reconstruction") |
| ax2.set_title("Evolution of the Loss") |
| return image_obj, image_ax, line |
| |
| def update_sdf(iteration, record, resolution, line, image_ax, image_obj, bbox): |
| image_iter = record[f"inboundary.dirichlet.tensor-{iteration}"].squeeze() |
| box_length = bbox[1][0] - bbox[0][0] |
| box_center = [(bbox[0][0] + bbox[1][0])/2, (bbox[0][1] + bbox[1][1])/2 ] |
| sdf = SDFGrid(image_iter, box_length=box_length, box_center = box_center) |
| fig, (ax_dummy) = plt.subplots(1, 1, figsize=[5, 5]) |
| if image_obj is not None: |
| image_obj_ = np.array(image_obj) |
| else: |
| image_obj_ = None |
| image_iter = sdf.sketch_image(ax_dummy, bbox, resolution, image = image_obj_, channel = 2) |
| plt.close(fig) |
| loss = record["loss"].sum(axis = 1)[:iteration] |
| iters = np.arange(iteration) |
| line.set_xdata(iters) |
| line.set_ydata(loss) |
| |
| image_ax.set_data(image_iter * 0.8) |
|
|
| def plot_summary(loss_list, loss_reg_list, path, log = False, save_npy = True): |
| losses = np.array(loss_list) |
| losses_reg = np.array(loss_reg_list) |
| if save_npy: |
| np.save(os.path.join(path, "losses.npy"),losses) |
| np.save(os.path.join(path, "losses_reg.npy"),losses_reg) |
