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import streamlit as st
import pickle
import io
from typing import List, Optional
import markdown
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import plotly.graph_objects as go
import streamlit as st
from plotly import express as px
from plotly.subplots import make_subplots
from tqdm import trange
import torch
from transformers import AutoFeatureExtractor, AutoModelForImageClassification
@st.cache(allow_output_mutation=True)
# @st.cache_resource
def load_dataset(data_index):
with open(f'./data/preprocessed_image_net/val_data_{data_index}.pkl', 'rb') as file:
dataset = pickle.load(file)
return dataset
@st.cache(allow_output_mutation=True)
# @st.cache_resource
def load_dataset_dict():
dataset_dict = {}
progress_empty = st.empty()
text_empty = st.empty()
text_empty.write("Loading datasets...")
progress_bar = progress_empty.progress(0.0)
for data_index in trange(5):
dataset_dict[data_index] = load_dataset(data_index)
progress_bar.progress((data_index+1)/5)
progress_empty.empty()
text_empty.empty()
return dataset_dict
# @st.cache_data
@st.cache(allow_output_mutation=True)
def load_image(image_id):
dataset = load_dataset(image_id//10000)
image = dataset[image_id%10000]
return image
# @st.cache_data
@st.cache(allow_output_mutation=True)
def load_images(image_ids):
images = []
for image_id in image_ids:
image = load_image(image_id)
images.append(image)
return images
@st.cache(allow_output_mutation=True, suppress_st_warning=True, show_spinner=False)
# @st.cache_resource
def load_model(model_name):
with st.spinner(f"Loading {model_name} model! This process might take 1-2 minutes..."):
if model_name == 'ResNet':
model_file_path = 'microsoft/resnet-50'
feature_extractor = AutoFeatureExtractor.from_pretrained(model_file_path, crop_pct=1.0)
model = AutoModelForImageClassification.from_pretrained(model_file_path)
model.eval()
elif model_name == 'ConvNeXt':
model_file_path = 'facebook/convnext-tiny-224'
feature_extractor = AutoFeatureExtractor.from_pretrained(model_file_path, crop_pct=1.0)
model = AutoModelForImageClassification.from_pretrained(model_file_path)
model.eval()
else:
model = torch.hub.load('pytorch/vision:v0.10.0', 'mobilenet_v2', pretrained=True)
model.eval()
feature_extractor = None
return model, feature_extractor
def make_grid(cols=None,rows=None):
grid = [0]*rows
for i in range(rows):
with st.container():
grid[i] = st.columns(cols)
return grid
def use_container_width_percentage(percentage_width:int = 75):
max_width_str = f"max-width: {percentage_width}%;"
st.markdown(f"""
<style>
.reportview-container .main .block-container{{{max_width_str}}}
</style>
""",
unsafe_allow_html=True,
)
matplotlib.use("Agg")
COLOR = "#31333f"
BACKGROUND_COLOR = "#ffffff"
def grid_demo():
"""Main function. Run this to run the app"""
st.sidebar.title("Layout and Style Experiments")
st.sidebar.header("Settings")
st.markdown(
"""
# Layout and Style Experiments
The basic question is: Can we create a multi-column dashboard with plots, numbers and text using
the [CSS Grid](https://gridbyexample.com/examples)?
Can we do it with a nice api?
Can have a dark theme?
"""
)
select_block_container_style()
add_resources_section()
# My preliminary idea of an API for generating a grid
with Grid("1 1 1", color=COLOR, background_color=BACKGROUND_COLOR) as grid:
grid.cell(
class_="a",
grid_column_start=2,
grid_column_end=3,
grid_row_start=1,
grid_row_end=2,
).markdown("# This is A Markdown Cell")
grid.cell("b", 2, 3, 2, 3).text("The cell to the left is a dataframe")
grid.cell("c", 3, 4, 2, 3).plotly_chart(get_plotly_fig())
grid.cell("d", 1, 2, 1, 3).dataframe(get_dataframe())
grid.cell("e", 3, 4, 1, 2).markdown(
"Try changing the **block container style** in the sidebar!"
)
grid.cell("f", 1, 3, 3, 4).text(
"The cell to the right is a matplotlib svg image"
)
grid.cell("g", 3, 4, 3, 4).pyplot(get_matplotlib_plt())
def add_resources_section():
"""Adds a resources section to the sidebar"""
st.sidebar.header("Add_resources_section")
st.sidebar.markdown(
"""
- [gridbyexample.com] (https://gridbyexample.com/examples/)
"""
)
class Cell:
"""A Cell can hold text, markdown, plots etc."""
def __init__(
self,
class_: str = None,
grid_column_start: Optional[int] = None,
grid_column_end: Optional[int] = None,
grid_row_start: Optional[int] = None,
grid_row_end: Optional[int] = None,
):
self.class_ = class_
self.grid_column_start = grid_column_start
self.grid_column_end = grid_column_end
self.grid_row_start = grid_row_start
self.grid_row_end = grid_row_end
self.inner_html = ""
def _to_style(self) -> str:
return f"""
.{self.class_} {{
grid-column-start: {self.grid_column_start};
grid-column-end: {self.grid_column_end};
grid-row-start: {self.grid_row_start};
grid-row-end: {self.grid_row_end};
}}
"""
def text(self, text: str = ""):
self.inner_html = text
def markdown(self, text):
self.inner_html = markdown.markdown(text)
def dataframe(self, dataframe: pd.DataFrame):
self.inner_html = dataframe.to_html()
def plotly_chart(self, fig):
self.inner_html = f"""
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
<body>
<p>This should have been a plotly plot.
But since *script* tags are removed when inserting MarkDown/ HTML i cannot get it to workto work.
But I could potentially save to svg and insert that.</p>
<div id='divPlotly'></div>
<script>
var plotly_data = {fig.to_json()}
Plotly.react('divPlotly', plotly_data.data, plotly_data.layout);
</script>
</body>
"""
def pyplot(self, fig=None, **kwargs):
string_io = io.StringIO()
plt.savefig(string_io, format="svg", fig=(2, 2))
svg = string_io.getvalue()[215:]
plt.close(fig)
self.inner_html = '<div height="200px">' + svg + "</div>"
def _to_html(self):
return f"""<div class="box {self.class_}">{self.inner_html}</div>"""
class Grid:
"""A (CSS) Grid"""
def __init__(
self,
template_columns="1 1 1",
gap="10px",
background_color=COLOR,
color=BACKGROUND_COLOR,
):
self.template_columns = template_columns
self.gap = gap
self.background_color = background_color
self.color = color
self.cells: List[Cell] = []
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
st.markdown(self._get_grid_style(), unsafe_allow_html=True)
st.markdown(self._get_cells_style(), unsafe_allow_html=True)
st.markdown(self._get_cells_html(), unsafe_allow_html=True)
def _get_grid_style(self):
return f"""
<style>
.wrapper {{
display: grid;
grid-template-columns: {self.template_columns};
grid-gap: {self.gap};
background-color: {self.color};
color: {self.background_color};
}}
.box {{
background-color: {self.color};
color: {self.background_color};
border-radius: 0px;
padding: 0px;
font-size: 100%;
text-align: center;
}}
table {{
color: {self.color}
}}
</style>
"""
def _get_cells_style(self):
return (
"<style>"
+ "\n".join([cell._to_style() for cell in self.cells])
+ "</style>"
)
def _get_cells_html(self):
return (
'<div class="wrapper">'
+ "\n".join([cell._to_html() for cell in self.cells])
+ "</div>"
)
def cell(
self,
class_: str = None,
grid_column_start: Optional[int] = None,
grid_column_end: Optional[int] = None,
grid_row_start: Optional[int] = None,
grid_row_end: Optional[int] = None,
):
cell = Cell(
class_=class_,
grid_column_start=grid_column_start,
grid_column_end=grid_column_end,
grid_row_start=grid_row_start,
grid_row_end=grid_row_end,
)
self.cells.append(cell)
return cell
def select_block_container_style():
"""Add selection section for setting setting the max-width and padding
of the main block container"""
st.sidebar.header("Block Container Style")
max_width_100_percent = st.sidebar.checkbox("Max-width: 100%?", False)
if not max_width_100_percent:
max_width = st.sidebar.slider("Select max-width in px", 100, 2000, 1200, 100)
else:
max_width = 1200
dark_theme = st.sidebar.checkbox("Dark Theme?", False)
padding_top = st.sidebar.number_input("Select padding top in rem", 0, 200, 5, 1)
padding_right = st.sidebar.number_input("Select padding right in rem", 0, 200, 1, 1)
padding_left = st.sidebar.number_input("Select padding left in rem", 0, 200, 1, 1)
padding_bottom = st.sidebar.number_input(
"Select padding bottom in rem", 0, 200, 10, 1
)
if dark_theme:
global COLOR
global BACKGROUND_COLOR
BACKGROUND_COLOR = "rgb(17,17,17)"
COLOR = "#fff"
_set_block_container_style(
max_width,
max_width_100_percent,
padding_top,
padding_right,
padding_left,
padding_bottom,
)
def _set_block_container_style(
max_width: int = 1200,
max_width_100_percent: bool = False,
padding_top: int = 5,
padding_right: int = 1,
padding_left: int = 1,
padding_bottom: int = 10,
):
if max_width_100_percent:
max_width_str = f"max-width: 100%;"
else:
max_width_str = f"max-width: {max_width}px;"
st.markdown(
f"""
<style>
.reportview-container .main .block-container{{
{max_width_str}
padding-top: {padding_top}rem;
padding-right: {padding_right}rem;
padding-left: {padding_left}rem;
padding-bottom: {padding_bottom}rem;
}}
.reportview-container .main {{
color: {COLOR};
background-color: {BACKGROUND_COLOR};
}}
</style>
""",
unsafe_allow_html=True,
)
# @st.cache
# def get_dataframe() -> pd.DataFrame():
# """Dummy DataFrame"""
# data = [
# {"quantity": 1, "price": 2},
# {"quantity": 3, "price": 5},
# {"quantity": 4, "price": 8},
# ]
# return pd.DataFrame(data)
# def get_plotly_fig():
# """Dummy Plotly Plot"""
# return px.line(data_frame=get_dataframe(), x="quantity", y="price")
# def get_matplotlib_plt():
# get_dataframe().plot(kind="line", x="quantity", y="price", figsize=(5, 3))
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