firelab-general/flask_frontend.py

67 lines
1.9 KiB
Python

from flask import Flask, render_template, request
import numpy as np
from ratio_pyrometry import ratio_pyrometry_pipeline
import base64
import cv2 as cv
import plotly.figure_factory as ff
from scipy import stats
app = Flask(
__name__,
static_folder='static',
static_url_path='/s/'
)
@app.route('/', methods=['GET'])
def index():
return render_template('index.jinja2')
@app.route('/ratio_pyro', methods=['POST'])
def ratio_pyro():
f = request.files['file']
f_bytes = np.fromstring(f.read(), np.uint8)
img_orig, img_res, key, ptemps = ratio_pyrometry_pipeline(
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']),
MIN_TEMP=float(request.form['min_temp']),
smoothing_radius=int(request.form['smoothing_radius']),
key_entries=int(request.form['legend_entries']),
eqn_scaling_factor=float(request.form['equation_scaling_factor'])
)
# 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')
# generate prob. distribution histogram & return embed
fig = ff.create_distplot(
[ptemps],
group_labels=[f.filename],
show_rug=False,
show_hist=False,
)
fig.update_layout(
autosize=False,
width=800,
height=600,
)
fig.update_xaxes(
title_text="Temperature (°C)",
)
fig.update_yaxes(
title_text="Probability (1/°C)",
)
freq_plot = fig.to_html()
return render_template(
'results.jinja2',
img_orig_b64=img_orig_b64,
img_res_b64=img_res_b64,
legend=key,
freq_plot=freq_plot
)