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| import gradio as gr | |
| import pandas as pd | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from mpl_toolkits.mplot3d import Axes3D | |
| from gradio.components import Slider, Number, Image, Dataframe, Textbox, Checkbox, Radio, Label, Plot | |
| import plotly.graph_objects as go | |
| from aaaaa import get_datXYZ, plot_3d_points, genS | |
| from scipy.stats import multivariate_normal | |
| import PIL.Image | |
| data_path = "reference_data/" | |
| image_path = "images_configs/" | |
| # To generate distorsed covariance matrixes | |
| def genS(sds, R, distor=1): | |
| # sds: standard deviations | |
| # R: correlation matrix | |
| # distor: level of distorsion | |
| sdsdis = sds * distor | |
| S = R * np.outer(sdsdis, sdsdis) | |
| np.fill_diagonal(S, sdsdis ** 2) | |
| return S | |
| def show_hand_3d(gesto, attempt, distortion, mean, std): | |
| datXYZ = get_datXYZ(gesto, data_path) | |
| print(datXYZ.shape) | |
| # print(datXYZ) | |
| obsmean = np.mean(datXYZ, axis=0) | |
| print(obsmean.shape) | |
| # change to 63 shape | |
| obsmean = obsmean.reshape(63) | |
| obssd = np.std(datXYZ, axis=0) | |
| print(obssd.shape) | |
| obssd = obssd.reshape(63) | |
| datXYZ_reshaped = datXYZ.reshape(datXYZ.shape[0], -1) | |
| R = np.corrcoef(datXYZ_reshaped, rowvar=False) | |
| Sberria = genS(obssd, R, distor=distortion) | |
| z = multivariate_normal.rvs(mean=obsmean, cov=Sberria, size=1) | |
| print(z.shape) | |
| # print(z) | |
| # add here the code to transform z into an array eith the same shape as datXYZ | |
| first_row = datXYZ[attempt] # Extract the attempt row of the array | |
| reshaped_array = first_row[:63].reshape(21, 3) # Reshape the first row to (21, 3) | |
| # create noise from mean and std | |
| noise = np.random.normal(mean, std, reshaped_array.shape) | |
| reshaped_array_with_noise = reshaped_array + noise | |
| distorted_hand = z.reshape(reshaped_array.shape) | |
| hand_plot = plot_3d_points(reshaped_array, "Recorded Hand Configuration") | |
| distorted_hand_plot = plot_3d_points(distorted_hand, "Distorted Hand Configuration (global)") | |
| reshaped_array_with_noise_plot = plot_3d_points(reshaped_array_with_noise, "Distorted Hand Configuration (individual))") | |
| image_filename = image_path + str(int(gesto)) + ".png" | |
| print(image_filename) | |
| image = PIL.Image.open(image_filename) | |
| # image = Image(image_filename) # Load the corresponding image | |
| return image, hand_plot, distorted_hand_plot, reshaped_array_with_noise_plot | |
| inputs = [ | |
| Number(value=42, precision=0, label="Number of Kind of Hand Configuration"), | |
| Number(value=0, precision=0, label="Number of Concrete Hand Attempt"), | |
| Number(value=1.0, label="Distortion Level"), | |
| Number(value=0.0, label="Mean Distortion Level (one hand)"), | |
| Number(value=0.006, label="Standard Deviation Distortion Level (one hand)") | |
| ] | |
| outputs = [Image(type="pil"), Plot(), Plot(), Plot()] | |
| title = "Hand 3D Visualization" | |
| description = "Enter the gesture number (gesto) and the data path (data_path) to visualize the hand in 3D." | |
| iface = gr.Interface(fn=show_hand_3d, | |
| inputs=inputs, | |
| outputs=outputs, | |
| title=title, | |
| description=description, | |
| allow_flagging="never") | |
| iface.launch() |