| 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 |
|
|
|
|
| @st.cache(allow_output_mutation=True, max_entries=10, ttl=3600) |
| 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 |
|
|
| |
| cropped_image = image.crop( |
| (left + 75, top + 145, right - 2025, bottom - (2915 + 25 + 10)) |
| ).resize((300, 300)) |
|
|
| return cropped_image |
|
|
|
|
| |
| @st.cache(allow_output_mutation=True, max_entries=10, ttl=3600) |
| 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 |
|
|
| |
| cropped_image = image.crop( |
| (left + 475, top + 140, right - 280, bottom - (2920 + 25 + 10)) |
| ) |
| return cropped_image |
|
|
|
|
| @st.cache(allow_output_mutation=True, max_entries=10, ttl=3600) |
| 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 |
|
|
| |
| cropped_image = image.crop( |
| (left + 475, top + 875, right - 280, bottom - (1810 + 25 + 10)) |
| ) |
| return cropped_image |
|
|
|
|
| |
|
|
| |
| @st.cache(allow_output_mutation=True, max_entries=10, ttl=3600) |
| 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 |
|
|
| |
| cropped_image = image.crop( |
| (left + 475, top + 510, right - 280, bottom - (2550 + 25 + 10)) |
| ) |
| return cropped_image |
|
|
|
|
| |
|
|
| |
| @st.cache(allow_output_mutation=True, max_entries=10, ttl=3600) |
| 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 |
|
|
| |
| cropped_image = image.crop( |
| (left + 10, top + 2075, right - 420, bottom - (925 + 25 + 10)) |
| ) |
| return cropped_image |
|
|
|
|
| @st.cache(allow_output_mutation=True, max_entries=10, ttl=3600) |
| 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 |
|
|
| |
| cropped_image = image.crop((left + 10, top + 2500, right - 20, bottom)) |
| return cropped_image |
|
|
|
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| |
|
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|
|
| @st.cache() |
| def convert_df(df): |
| return df.to_csv().encode("utf-8") |
|
|
