67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
from flask import Flask, render_template, request
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import numpy as np
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from ratio_pyrometry import ratio_pyrometry_pipeline
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import base64
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import cv2 as cv
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import plotly.figure_factory as ff
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from scipy import stats
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app = Flask(
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__name__,
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static_folder='static',
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static_url_path='/s/'
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)
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@app.route('/', methods=['GET'])
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def index():
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return render_template('index.jinja2')
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@app.route('/ratio_pyro', methods=['POST'])
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def ratio_pyro():
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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,
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ISO=float(request.form['iso']),
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I_Darkcurrent=float(request.form['i_darkcurrent']),
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exposure_time=float(request.form['exposure_time']),
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f_stop=float(request.form['f_stop']),
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MAX_TEMP=float(request.form['max_temp']),
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MIN_TEMP=float(request.form['min_temp']),
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smoothing_radius=int(request.form['smoothing_radius']),
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key_entries=int(request.form['legend_entries']),
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eqn_scaling_factor=float(request.form['equation_scaling_factor'])
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)
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# get base64 encoded images
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img_orig_b64 = base64.b64encode(cv.imencode('.png', img_orig)[1]).decode(encoding='utf-8')
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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
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fig = ff.create_distplot(
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[ptemps],
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group_labels=[f.name],
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show_rug=False,
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show_hist=False,
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)
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fig.update_layout(
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autosize=False,
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width=800,
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height=600,
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)
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fig.update_xaxes(
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title_text="Temperature (°C)",
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)
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fig.update_xaxes(
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title_text="Probability (1/°C)",
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)
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freq_plot = fig.to_html()
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return render_template(
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'results.jinja2',
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img_orig_b64=img_orig_b64,
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img_res_b64=img_res_b64,
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legend=key,
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freq_plot=freq_plot
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)
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