firelab-general/flask_frontend.py

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from flask import Flask, render_template, request, send_file
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import numpy as np
from ratio_pyrometry import ratio_pyrometry_pipeline
from size_projection import get_projected_area
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import base64
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import cv2 as cv
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import plotly.figure_factory as ff
import pandas as pd
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app = Flask(
__name__,
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static_folder='static',
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static_url_path='/s/'
)
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@app.route('/', methods=['GET'])
def index():
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return render_template('index.html')
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@app.route('/ratio_pyro', methods=['POST'])
def ratio_pyro():
f = request.files['file']
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f_bytes = np.fromstring(f.read(), np.uint8)
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img_orig, img_res, key, ptemps = ratio_pyrometry_pipeline(
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f_bytes,
ISO=float(request.form['iso']),
I_Darkcurrent=float(request.form['i_darkcurrent']),
exposure_time=float(request.form['exposure_time']),
f_stop=float(request.form['f_stop']),
MAX_TEMP=float(request.form['max_temp']),
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MIN_TEMP=float(request.form['min_temp']),
smoothing_radius=int(request.form['smoothing_radius']),
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key_entries=int(request.form['legend_entries']),
eqn_scaling_factor=float(request.form['equation_scaling_factor'])
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)
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# get base64 encoded images
img_orig_b64 = base64.b64encode(cv.imencode('.png', img_orig)[1]).decode(encoding='utf-8')
img_res_b64 = base64.b64encode(cv.imencode('.png', img_res)[1]).decode(encoding='utf-8')
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# generate prob. distribution histogram & return embed
fig = ff.create_distplot(
[ptemps],
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group_labels=[f.filename],
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show_rug=False,
show_hist=False,
)
fig.update_layout(
autosize=False,
width=800,
height=600,
)
fig.update_xaxes(
title_text="Temperature (°C)",
)
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fig.update_yaxes(
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title_text="Probability (1/°C)",
)
freq_plot = fig.to_html()
# create csv-formatted stuff
# currently only supports 1 firebrand (grabs first object in plot).
plot_data=fig.to_dict()
x_data = plot_data["data"][0]["x"]
y_data = plot_data["data"][0]["y"]
tdata = [["Temperature", "Frequency"]]
for i in range(len(x_data)):
r = []
r.append(x_data[i])
r.append(y_data[i])
tdata.append(r)
csvstr = pd.DataFrame(tdata).to_csv(index=False, header=False)
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return render_template(
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'pyrometry-results.html',
img_orig_b64=img_orig_b64,
img_res_b64=img_res_b64,
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legend=key,
freq_plot=freq_plot,
csv_data=csvstr
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)
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@app.route('/projected_area')
def projected_area():
return render_template('projected-area.html')
@app.route('/projected_area_results', methods=['POST'])
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def projected_area_results():
f = request.files['file']
f_bytes = np.fromstring(f.read(), np.uint8)
img, dtable = get_projected_area(
f_bytes,
int(request.form['area_threshold']),
int(request.form['min_display_threshold']),
float(request.form['paper_width']),
float(request.form['paper_width'])
)
return render_template(
'projected-area-results.html',
img_b64=img,
dtable=dtable
)
# @app.route("/download_pyrometry_temps")
# def download_pyrometry_temps():
# return send_file()