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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() |