restructure, start flask stuff

examples/grayscale_pyrometry.py

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+import cv2 as cv
+import numpy as np
+
+img = cv.imread('01-0001.png', 0)
+
+kernel = np.array([
+    [1.3]
+])
+img = cv.filter2D(src=img, ddepth=-1, kernel=kernel)
+
+img = cv.applyColorMap(img, cv.COLORMAP_JET)
+cv.imwrite('01-0001-transformed-grayscale.png', img)

examples/ratio_pyrometry.py

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+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))

examples/ratio_pyrometry_legend.py

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+import ratio_pyrometry
+
+@jit(nopython=True)
+def normalization_func_customizable(i, I_Darkcurrent, ISO, f_stop, exposure_time):
+    return (i - I_Darkcurrent) * (f_stop ** 2) / (ISO * exposure_time)
+
+