restructure, start flask stuff

.gitignore

@@ -2,7 +2,8 @@
 
 .vscode/
 *.swp
-
+uploads/*
+!uploads/.gitkeep
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

Pipfile

@@ -6,6 +6,9 @@ name = "pypi"
 [packages]
 opencv-python = "*"
 numba = "*"
+flask = "*"
+gunicorn = "*"
+werkzeug = "*"
 
 [dev-packages]
 

Pipfile.lock

@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "4d38c8456723919069d64e7e19fd21317602969788feb71d5a4b4bbd183adcf2"
+            "sha256": "f32b823e3975ed0083bf7bedff36887eb3c9a01fe41b0e9142630b508e63692a"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -16,6 +16,46 @@
         ]
     },
     "default": {
+        "click": {
+            "hashes": [
+                "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e",
+                "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==8.1.3"
+        },
+        "flask": {
+            "hashes": [
+                "sha256:642c450d19c4ad482f96729bd2a8f6d32554aa1e231f4f6b4e7e5264b16cca2b",
+                "sha256:b9c46cc36662a7949f34b52d8ec7bb59c0d74ba08ba6cb9ce9adc1d8676d9526"
+            ],
+            "index": "pypi",
+            "version": "==2.2.2"
+        },
+        "gunicorn": {
+            "hashes": [
+                "sha256:9dcc4547dbb1cb284accfb15ab5667a0e5d1881cc443e0677b4882a4067a807e",
+                "sha256:e0a968b5ba15f8a328fdfd7ab1fcb5af4470c28aaf7e55df02a99bc13138e6e8"
+            ],
+            "index": "pypi",
+            "version": "==20.1.0"
+        },
+        "itsdangerous": {
+            "hashes": [
+                "sha256:2c2349112351b88699d8d4b6b075022c0808887cb7ad10069318a8b0bc88db44",
+                "sha256:5dbbc68b317e5e42f327f9021763545dc3fc3bfe22e6deb96aaf1fc38874156a"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==2.1.2"
+        },
+        "jinja2": {
+            "hashes": [
+                "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852",
+                "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==3.1.2"
+        },
         "llvmlite": {
             "hashes": [
                 "sha256:03aee0ccd81735696474dc4f8b6be60774892a2929d6c05d093d17392c237f32",
@@ -50,6 +90,52 @@
             "markers": "python_version >= '3.7'",
             "version": "==0.39.1"
         },
+        "markupsafe": {
+            "hashes": [
+                "sha256:0212a68688482dc52b2d45013df70d169f542b7394fc744c02a57374a4207003",
+                "sha256:089cf3dbf0cd6c100f02945abeb18484bd1ee57a079aefd52cffd17fba910b88",
+                "sha256:10c1bfff05d95783da83491be968e8fe789263689c02724e0c691933c52994f5",
+                "sha256:33b74d289bd2f5e527beadcaa3f401e0df0a89927c1559c8566c066fa4248ab7",
+                "sha256:3799351e2336dc91ea70b034983ee71cf2f9533cdff7c14c90ea126bfd95d65a",
+                "sha256:3ce11ee3f23f79dbd06fb3d63e2f6af7b12db1d46932fe7bd8afa259a5996603",
+                "sha256:421be9fbf0ffe9ffd7a378aafebbf6f4602d564d34be190fc19a193232fd12b1",
+                "sha256:43093fb83d8343aac0b1baa75516da6092f58f41200907ef92448ecab8825135",
+                "sha256:46d00d6cfecdde84d40e572d63735ef81423ad31184100411e6e3388d405e247",
+                "sha256:4a33dea2b688b3190ee12bd7cfa29d39c9ed176bda40bfa11099a3ce5d3a7ac6",
+                "sha256:4b9fe39a2ccc108a4accc2676e77da025ce383c108593d65cc909add5c3bd601",
+                "sha256:56442863ed2b06d19c37f94d999035e15ee982988920e12a5b4ba29b62ad1f77",
+                "sha256:671cd1187ed5e62818414afe79ed29da836dde67166a9fac6d435873c44fdd02",
+                "sha256:694deca8d702d5db21ec83983ce0bb4b26a578e71fbdbd4fdcd387daa90e4d5e",
+                "sha256:6a074d34ee7a5ce3effbc526b7083ec9731bb3cbf921bbe1d3005d4d2bdb3a63",
+                "sha256:6d0072fea50feec76a4c418096652f2c3238eaa014b2f94aeb1d56a66b41403f",
+                "sha256:6fbf47b5d3728c6aea2abb0589b5d30459e369baa772e0f37a0320185e87c980",
+                "sha256:7f91197cc9e48f989d12e4e6fbc46495c446636dfc81b9ccf50bb0ec74b91d4b",
+                "sha256:86b1f75c4e7c2ac2ccdaec2b9022845dbb81880ca318bb7a0a01fbf7813e3812",
+                "sha256:8dc1c72a69aa7e082593c4a203dcf94ddb74bb5c8a731e4e1eb68d031e8498ff",
+                "sha256:8e3dcf21f367459434c18e71b2a9532d96547aef8a871872a5bd69a715c15f96",
+                "sha256:8e576a51ad59e4bfaac456023a78f6b5e6e7651dcd383bcc3e18d06f9b55d6d1",
+                "sha256:96e37a3dc86e80bf81758c152fe66dbf60ed5eca3d26305edf01892257049925",
+                "sha256:97a68e6ada378df82bc9f16b800ab77cbf4b2fada0081794318520138c088e4a",
+                "sha256:99a2a507ed3ac881b975a2976d59f38c19386d128e7a9a18b7df6fff1fd4c1d6",
+                "sha256:a49907dd8420c5685cfa064a1335b6754b74541bbb3706c259c02ed65b644b3e",
+                "sha256:b09bf97215625a311f669476f44b8b318b075847b49316d3e28c08e41a7a573f",
+                "sha256:b7bd98b796e2b6553da7225aeb61f447f80a1ca64f41d83612e6139ca5213aa4",
+                "sha256:b87db4360013327109564f0e591bd2a3b318547bcef31b468a92ee504d07ae4f",
+                "sha256:bcb3ed405ed3222f9904899563d6fc492ff75cce56cba05e32eff40e6acbeaa3",
+                "sha256:d4306c36ca495956b6d568d276ac11fdd9c30a36f1b6eb928070dc5360b22e1c",
+                "sha256:d5ee4f386140395a2c818d149221149c54849dfcfcb9f1debfe07a8b8bd63f9a",
+                "sha256:dda30ba7e87fbbb7eab1ec9f58678558fd9a6b8b853530e176eabd064da81417",
+                "sha256:e04e26803c9c3851c931eac40c695602c6295b8d432cbe78609649ad9bd2da8a",
+                "sha256:e1c0b87e09fa55a220f058d1d49d3fb8df88fbfab58558f1198e08c1e1de842a",
+                "sha256:e72591e9ecd94d7feb70c1cbd7be7b3ebea3f548870aa91e2732960fa4d57a37",
+                "sha256:e8c843bbcda3a2f1e3c2ab25913c80a3c5376cd00c6e8c4a86a89a28c8dc5452",
+                "sha256:efc1913fd2ca4f334418481c7e595c00aad186563bbc1ec76067848c7ca0a933",
+                "sha256:f121a1420d4e173a5d96e47e9a0c0dcff965afdf1626d28de1460815f7c4ee7a",
+                "sha256:fc7b548b17d238737688817ab67deebb30e8073c95749d55538ed473130ec0c7"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==2.1.1"
+        },
         "numba": {
             "hashes": [
                 "sha256:0c358fd4ef7c5efc09ee96432284d66df285bd68654e85c39cf6c570dc35429a",
@@ -115,7 +201,7 @@
                 "sha256:f8c02ec3c4c4fcb718fdf89a6c6f709b14949408e8cf2a2be5bfa9c49548fd85",
                 "sha256:ffcf105ecdd9396e05a8e58e81faaaf34d3f9875f137c7372450baa5d77c9a54"
             ],
-            "markers": "python_version >= '3.10'",
+            "markers": "python_version >= '3.7'",
             "version": "==1.23.3"
         },
         "opencv-python": {
@@ -138,6 +224,14 @@
             ],
             "markers": "python_version >= '3.7'",
             "version": "==59.8.0"
+        },
+        "werkzeug": {
+            "hashes": [
+                "sha256:7ea2d48322cc7c0f8b3a215ed73eabd7b5d75d0b50e31ab006286ccff9e00b8f",
+                "sha256:f979ab81f58d7318e064e99c4506445d60135ac5cd2e177a2de0089bfd4c9bd5"
+            ],
+            "index": "pypi",
+            "version": "==2.2.2"
         }
     },
     "develop": {}

display_key.html

@@ -7,26 +7,6 @@
         <td class="legend-cell"><div style="width:20px;height:20px;background-color:rgb(256, 176, 0);"></div></td>
         <td class="legend-cell">0°C</td>
     </tr>
-    <tr>
-        <td class="legend-cell"><div style="width:20px;height:20px;background-color:rgb(168, 0, 0);"></div></td>
-        <td class="legend-cell">800°C</td>
-    </tr>
-    <tr>
-        <td class="legend-cell"><div style="width:20px;height:20px;background-color:rgb(0, 96, 255);"></div></td>
-        <td class="legend-cell">900°C</td>
-    </tr>
-    <tr>
-        <td class="legend-cell"><div style="width:20px;height:20px;background-color:rgb(106, 255, 150);"></div></td>
-        <td class="legend-cell">1000°C</td>
-    </tr>
-    <tr>
-        <td class="legend-cell"><div style="width:20px;height:20px;background-color:rgb(255, 136, 0);"></div></td>
-        <td class="legend-cell">1000°C</td>
-    </tr>
-    <tr>
-        <td class="legend-cell"><div style="width:20px;height:20px;background-color:rgb(128, 0, 0);"></div></td>
-        <td class="legend-cell">1000°C</td>
-    </tr>
 </table>
 
 <style>

examples/ratio_pyrometry.py

@@ -0,0 +1,138 @@
+import math
+import cv2 as cv
+import numpy as np
+from numba import jit
+import json
+
+# camera settings
+file = '01-0001.png'
+I_Darkcurrent = 150.5
+exposure_time = 0.500
+f_stop = 2.4
+ISO = 64 # basically brightness
+
+# pyrometry config
+MAX_TEMP = 1200
+MIN_TEMP = 60
+# original range from paper
+# MAX_GR_RATIO = 1200
+# MIN_GR_RATIO = 600
+
+# Cropping config
+x1 = 420
+x2 = 1200
+y1 = 400
+y2 = -1
+
+# post-processing
+smoothing_radius = 2
+
+# temperature key generation
+key_entries = 6
+
+
+@jit(nopython=True)
+def rg_ratio_normalize(imgarr):
+    # set max & min to most extreme values, 
+    # work up & down respectively from there
+    tmin = MAX_TEMP
+    tmax = 0
+
+    imgnew = imgarr
+    for i in range(len(imgarr)):
+        for j in range(len(imgarr[i])):
+            px = imgarr[i][j]
+            r_norm = normalization_func(px[0])
+            g_norm = normalization_func(px[1])
+
+            # apply camera calibration func
+            temp_C = pyrometry_calibration_formula(g_norm, r_norm)
+
+            # remove pixels outside calibration range
+            if MAX_TEMP != None and temp_C > MAX_TEMP or MIN_TEMP != None and temp_C < MIN_TEMP:
+                temp_C = 0
+
+            # update min & max
+            if temp_C < tmin and temp_C >= 0:
+                tmin = temp_C
+            if temp_C > tmax:
+                tmax = temp_C
+
+            imgnew[i][j] = [temp_C, temp_C, temp_C]
+    return imgnew, tmin, tmax
+
+
+@jit(nopython=True)
+def normalization_func(i):
+    """
+    does something to the pixels that i don't understand lol
+    """
+    return (i - I_Darkcurrent) * (f_stop ** 2) / (ISO * exposure_time)
+
+
+@jit(nopython=True)
+def pyrometry_calibration_formula(i_ng, i_nr):
+    """
+    Given the green-red ratio, calculates an approximate temperature 
+    in Celsius.
+    """
+    return 362.73 * math.log10(
+        (i_ng/i_nr) ** 3
+    ) + 2186.7 * math.log10(
+        (i_ng/i_nr) ** 3
+    ) + 4466.5 * math.log10(
+        (i_ng / i_nr) ** 3
+    ) + 3753.5
+
+
+# read image & crop
+file_name = file.split(".")[0]
+file_ext = file.split(".")[1]
+img = cv.imread(file)
+img = img[y1:y2, x1:x2]
+cv.imwrite(f'{file_name}-cropped.{file_ext}', img)
+
+# img = cv.imread('ember_test.png')
+
+img, tmin, tmax = rg_ratio_normalize(img)
+
+print(f"min: {tmin}°C")
+print(f"max: {tmax}°C")
+
+# build & apply smoothing conv kernel
+k = []
+for i in range(smoothing_radius):
+    k.append([1/(smoothing_radius**2) for i in range(smoothing_radius)])
+kernel = np.array(k)
+
+img = cv.filter2D(src=img, ddepth=-1, kernel=kernel)
+
+# write colormapped image
+img_jet = cv.applyColorMap(img, cv.COLORMAP_JET)
+cv.imwrite(f'{file_name}-cropped-transformed-ratio.{file_ext}', img_jet)
+
+# --- Generate temperature key ---
+
+# adjust max & min temps to be the same as the image
+# tmin_adj = tmin / (smoothing_radius ** 2)
+# tmax_adj = tmax / (smoothing_radius ** 2)
+# Generate 6-step key
+step = (tmax - tmin) / (key_entries-1)
+temps = []
+key_img_arr = [[]]
+for i in range(key_entries):
+    res_temp = tmin + (i * step)
+    res_color = (tmax - (i * step)) / MAX_TEMP * 255
+    temps.append(res_temp)
+    key_img_arr[0].append([res_color, res_color, res_color])
+
+key_img = np.array(key_img_arr).astype(np.uint8)
+key_img_jet = cv.applyColorMap(key_img, cv.COLORMAP_JET)
+# cv.imwrite(f'{file_name}-key.{file_ext}', key_img_jet)
+
+tempkey = {}
+for i in range(len(temps)):
+    c = key_img_jet[0][i]
+    tempkey[temps[i]] = f"rgb({c[0]}, {c[1]}, {c[2]})"
+
+print(json.dumps(tempkey, indent=4))

flask_frontend.py

@@ -0,0 +1,16 @@
+from flask import Flask, render_template, request
+
+app = Flask(__name__)
+
+@app.route('/', methods=['GET'])
+def index():
+    return render_template('index.html')
+
+@app.route('/ratio_pyro', methods=['POST'])
+def ratio_pyro():
+    f = request.files['file']
+    I_Darkcurrent = 150.5
+    exposure_time = 0.500
+    f_stop = 2.4
+    ISO = 64 
+    return 200

ratio_pyrometry.py

@@ -84,58 +84,50 @@ def pyrometry_calibration_formula(i_ng, i_nr):
         (i_ng / i_nr) ** 3
     ) + 3753.5
 
+def ratio_pyrometry_pipeline(file):
 
-# read image & crop
+    # read image & crop
-file_name = file.split(".")[0]
+    file_name = file.split(".")[0]
-file_ext = file.split(".")[1]
+    file_ext = file.split(".")[1]
-img = cv.imread(file)
+    img = cv.imread(file)
-img = img[y1:y2, x1:x2]
+    img = img[y1:y2, x1:x2]
-cv.imwrite(f'{file_name}-cropped.{file_ext}', img)
+    cv.imwrite(f'{file_name}-cropped.{file_ext}', img)
 
-# img = cv.imread('ember_test.png')
+    # img = cv.imread('ember_test.png')
 
-img, tmin, tmax = rg_ratio_normalize(img)
+    img, tmin, tmax = rg_ratio_normalize(img)
 
-print(f"min: {tmin}°C")
+    # build & apply smoothing conv kernel
-print(f"max: {tmax}°C")
+    k = []
-
+    for i in range(smoothing_radius):
-# build & apply smoothing conv kernel
-k = []
-for i in range(smoothing_radius):
         k.append([1/(smoothing_radius**2) for i in range(smoothing_radius)])
-kernel = np.array(k)
+    kernel = np.array(k)
 
-img = cv.filter2D(src=img, ddepth=-1, kernel=kernel)
+    img = cv.filter2D(src=img, ddepth=-1, kernel=kernel)
 
-# write colormapped image
+    # write colormapped image
-img_jet = cv.applyColorMap(img, cv.COLORMAP_JET)
+    img_jet = cv.applyColorMap(img, cv.COLORMAP_JET)
-cv.imwrite(f'{file_name}-cropped-transformed-ratio.{file_ext}', img_jet)
+    cv.imwrite(f'{file_name}-cropped-transformed-ratio.{file_ext}', img_jet)
 
-# --- Generate temperature key ---
+    # --- Generate temperature key ---
 
-# adjust max & min temps to be the same as the image
+    # adjust max & min temps to be the same as the image
-# tmin_adj = tmin / (smoothing_radius ** 2)
+    # tmin_adj = tmin / (smoothing_radius ** 2)
-# tmax_adj = tmax / (smoothing_radius ** 2)
+    # tmax_adj = tmax / (smoothing_radius ** 2)
-# Generate 6-step key
+    # Generate 6-step key
-step = (tmax - tmin) / (key_entries-1)
+    step = (tmax - tmin) / (key_entries-1)
-temps = []
+    temps = []
-key_img_arr = [[]]
+    key_img_arr = [[]]
-for i in range(key_entries):
+    for i in range(key_entries):
         res_temp = tmin + (i * step)
         res_color = (tmax - (i * step)) / MAX_TEMP * 255
         temps.append(res_temp)
         key_img_arr[0].append([res_color, res_color, res_color])
 
-key_img = np.array(key_img_arr).astype(np.uint8)
+    key_img = np.array(key_img_arr).astype(np.uint8)
-key_img_jet = cv.applyColorMap(key_img, cv.COLORMAP_JET)
+    key_img_jet = cv.applyColorMap(key_img, cv.COLORMAP_JET)
-# cv.imwrite(f'{file_name}-key.{file_ext}', key_img_jet)
 
-tempkey = {}
+    tempkey = {}
-for i in range(len(temps)):
+    for i in range(len(temps)):
         c = key_img_jet[0][i]
         tempkey[temps[i]] = f"rgb({c[0]}, {c[1]}, {c[2]})"
-
-# with open(f"{file_name}-tempkey.json", "w+") as file_out:
-#     json.dump(tempkey, file_out)
-
-print(json.dumps(tempkey, indent=4))

templates/app.css

@@ -0,0 +1,4 @@
+.form {
+    display: flex;
+    flex-direction: column;
+}

templates/base.jinja2

@@ -0,0 +1,8 @@
+<!DOCTYPE html>
+<head>
+    <title>Pyrometry Application</title>
+    <link rel="app.css">
+</head>
+<body>
+    {% block content %}
+</body>

templates/index.jinja2

@@ -0,0 +1,7 @@
+{% extends "base.html" %}
+{% block content %} 
+    <div class="form">
+        <button onclick="">
+        </button>
+    </div>
+{% endblock %}