Spaces:
Runtime error
Runtime error
import json | |
import os | |
import pickle | |
import random | |
from glob import glob | |
import matplotlib.pyplot as plt | |
import pandas as pd | |
import seaborn as sns | |
import streamlit as st | |
from PIL import Image | |
def load_query(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
new_width = width | |
new_height = height | |
left = (width - new_width) / 2 | |
top = (height - new_height) / 2 | |
right = (width + new_width) / 2 | |
bottom = (height + new_height) / 2 | |
# Crop the center of the image | |
cropped_image = image.crop( | |
(left + 75, top + 145, right - 2025, bottom - (2915 + 25 + 10)) | |
).resize((300, 300)) | |
return cropped_image | |
# CHM ############################################################################ | |
def load_chm_nns(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
new_width = width | |
new_height = height | |
left = (width - new_width) / 2 | |
top = (height - new_height) / 2 | |
right = (width + new_width) / 2 | |
bottom = (height + new_height) / 2 | |
# Crop the center of the image | |
cropped_image = image.crop( | |
(left + 475, top + 140, right - 280, bottom - (2920 + 25 + 10)) | |
) | |
return cropped_image | |
def load_chm_corrs(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
new_width = width | |
new_height = height | |
left = (width - new_width) / 2 | |
top = (height - new_height) / 2 | |
right = (width + new_width) / 2 | |
bottom = (height + new_height) / 2 | |
# Crop the center of the image | |
cropped_image = image.crop( | |
(left + 475, top + 875, right - 280, bottom - (1810 + 25 + 10)) | |
) | |
return cropped_image | |
# CHM ############################################################################ | |
# KNN ############################################################################ | |
def load_knn_nns(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
new_width = width | |
new_height = height | |
left = (width - new_width) / 2 | |
top = (height - new_height) / 2 | |
right = (width + new_width) / 2 | |
bottom = (height + new_height) / 2 | |
# Crop the center of the image | |
cropped_image = image.crop( | |
(left + 475, top + 510, right - 280, bottom - (2550 + 25 + 10)) | |
) | |
return cropped_image | |
# KNN ############################################################################ | |
# EMD ############################################################################ | |
def load_emd_nns(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
new_width = width | |
new_height = height | |
left = (width - new_width) / 2 | |
top = (height - new_height) / 2 | |
right = (width + new_width) / 2 | |
bottom = (height + new_height) / 2 | |
# Crop the center of the image | |
cropped_image = image.crop( | |
(left + 10, top + 2075, right - 420, bottom - (925 + 25 + 10)) | |
) | |
return cropped_image | |
def load_emd_corrs(image_path): | |
image = Image.open(image_path) | |
width, height = image.size | |
new_width = width | |
new_height = height | |
left = (width - new_width) / 2 | |
top = (height - new_height) / 2 | |
right = (width + new_width) / 2 | |
bottom = (height + new_height) / 2 | |
# Crop the center of the image | |
cropped_image = image.crop((left + 10, top + 2500, right - 20, bottom)) | |
return cropped_image | |
# EMD ############################################################################ | |
def convert_df(df): | |
return df.to_csv().encode("utf-8") | |