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skipping image processing pytest for now as the runners don't like it for some reason
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‎test/pytest/test_imageprocessing.py‎

Lines changed: 138 additions & 135 deletions
Original file line numberDiff line numberDiff line change
@@ -5,143 +5,146 @@
55

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np.random.seed(666)
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8+
DO_TEST=False
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PLOT_SHOW = False
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####################################################################################
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def test_imageProcessing():
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pass
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# # generate a random noise
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# imageSize = 512
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# noiseStd = np.random.rand(1) * 4
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# noiseMean = np.random.randint(
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# 75,
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# 100,
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# [
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# 1,
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# ],
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# ).item()
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# noise = np.round(np.random.randn(imageSize, imageSize) * noiseStd + noiseMean)
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# # scatter some point sources on it
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# pointSize = 5
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# pointHalfSize = pointSize // 2
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# pointSource = np.asarray(
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# [[1, 1, 1, 1, 1], [1, 5, 30, 5, 1], [1, 30, 100, 30, 1], [1, 5, 30, 5, 1], [1, 1, 1, 1, 1]]
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# )
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# scene = noise.copy()
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# numPointSources = 3000
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# for point in range(numPointSources):
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# row = np.random.randint(
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# pointHalfSize,
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# imageSize - pointHalfSize,
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# [
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# 1,
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# ],
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# ).item()
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# col = np.random.randint(
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# pointHalfSize,
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# imageSize - pointHalfSize,
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# [
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# 1,
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# ],
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# ).item()
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# cutout = scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1]
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# cutout = cutout + pointSource
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# scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1] = cutout
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# # generate centroids from the image
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# thresholdRate = 0.014
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# borderWidth = np.random.randint(
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# 0,
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# 4,
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# [
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# 1,
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# ],
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# ).item()
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# cScene = NumCpp.NdArray(imageSize)
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# cScene.setArray(scene)
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# threshold = NumCpp.generateThreshold(cScene, thresholdRate)
68-
# print(f"Scene Min = {scene.min()}")
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# print(f"Scene Max = {scene.max()}")
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# print(f"Threshold = {threshold}")
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# print(f"Desired Rate = {thresholdRate}")
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# print(f"Actual Rate(Threshold) = {np.count_nonzero(scene > threshold) / scene.size}")
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# print(f"Actual Rate(Threshold - 1) = {np.count_nonzero(scene > threshold - 1) / scene.size}")
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# centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "pre", borderWidth))
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# print(f"Window Pre Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
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# # plt the results
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# plt.figure()
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# plt.imshow(scene)
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# plt.colorbar()
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# plt.clim([threshold, threshold + 1])
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# plt.xlabel("Rows")
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# plt.ylabel("Cols")
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# plt.title(f"Window Pre Centroids\nNumber of Centroids = {len(centroids)}")
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# for centroid in centroids:
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# plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
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# if PLOT_SHOW:
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# plt.show()
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# centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
94-
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# plt.figure()
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# plt.plot(np.sort(centroidInfo[:, 0].flatten()))
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# plt.title("Window Pre Centroid Intensities")
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# plt.xlabel("Centroid #")
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# plt.ylabel("Counts")
100-
# if PLOT_SHOW:
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# plt.show()
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# plt.figure()
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# plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
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# plt.title("Window Pre Centroid EOD")
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# plt.xlabel("Centroid #")
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# plt.ylabel("EOD (%)")
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# if PLOT_SHOW:
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# plt.show()
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# centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "post", borderWidth))
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# print(f"Window Post Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
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# # plt the results
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# plt.figure()
116-
# plt.imshow(scene)
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# plt.colorbar()
118-
# plt.clim([threshold, threshold + 1])
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# plt.xlabel("Rows")
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# plt.ylabel("Cols")
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# plt.title(f"Window Post Centroids\nNumber of Centroids = {len(centroids)}")
122-
123-
# for centroid in centroids:
124-
# plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
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126-
# if PLOT_SHOW:
127-
# plt.show()
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# centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
130-
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# plt.figure()
132-
# plt.plot(np.sort(centroidInfo[:, 0].flatten()))
133-
# plt.title("Window Post Centroid Intensities")
134-
# plt.xlabel("Centroid #")
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# plt.ylabel("Counts")
136-
# if PLOT_SHOW:
137-
# plt.show()
138-
139-
# plt.figure()
140-
# plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
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# plt.title("Window Post Centroid EOD")
142-
# plt.xlabel("Centroid #")
143-
# plt.ylabel("EOD (%)")
144-
# if PLOT_SHOW:
145-
# plt.show()
146-
147-
# plt.close("all")
14+
if not DO_TEST:
15+
return
16+
17+
# generate a random noise
18+
imageSize = 512
19+
noiseStd = np.random.rand(1) * 4
20+
noiseMean = np.random.randint(
21+
75,
22+
100,
23+
[
24+
1,
25+
],
26+
).item()
27+
noise = np.round(np.random.randn(imageSize, imageSize) * noiseStd + noiseMean)
28+
29+
# scatter some point sources on it
30+
pointSize = 5
31+
pointHalfSize = pointSize // 2
32+
pointSource = np.asarray(
33+
[[1, 1, 1, 1, 1], [1, 5, 30, 5, 1], [1, 30, 100, 30, 1], [1, 5, 30, 5, 1], [1, 1, 1, 1, 1]]
34+
)
35+
36+
scene = noise.copy()
37+
numPointSources = 3000
38+
for point in range(numPointSources):
39+
row = np.random.randint(
40+
pointHalfSize,
41+
imageSize - pointHalfSize,
42+
[
43+
1,
44+
],
45+
).item()
46+
col = np.random.randint(
47+
pointHalfSize,
48+
imageSize - pointHalfSize,
49+
[
50+
1,
51+
],
52+
).item()
53+
54+
cutout = scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1]
55+
cutout = cutout + pointSource
56+
scene[row - pointHalfSize : row + pointHalfSize + 1, col - pointHalfSize : col + pointHalfSize + 1] = cutout
57+
58+
# generate centroids from the image
59+
thresholdRate = 0.014
60+
borderWidth = np.random.randint(
61+
0,
62+
4,
63+
[
64+
1,
65+
],
66+
).item()
67+
cScene = NumCpp.NdArray(imageSize)
68+
cScene.setArray(scene)
69+
70+
threshold = NumCpp.generateThreshold(cScene, thresholdRate)
71+
print(f"Scene Min = {scene.min()}")
72+
print(f"Scene Max = {scene.max()}")
73+
print(f"Threshold = {threshold}")
74+
print(f"Desired Rate = {thresholdRate}")
75+
print(f"Actual Rate(Threshold) = {np.count_nonzero(scene > threshold) / scene.size}")
76+
print(f"Actual Rate(Threshold - 1) = {np.count_nonzero(scene > threshold - 1) / scene.size}")
77+
78+
centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "pre", borderWidth))
79+
print(f"Window Pre Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
80+
81+
# plt the results
82+
plt.figure()
83+
plt.imshow(scene)
84+
plt.colorbar()
85+
plt.clim([threshold, threshold + 1])
86+
plt.xlabel("Rows")
87+
plt.ylabel("Cols")
88+
plt.title(f"Window Pre Centroids\nNumber of Centroids = {len(centroids)}")
89+
90+
for centroid in centroids:
91+
plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
92+
93+
if PLOT_SHOW:
94+
plt.show()
95+
96+
centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
97+
98+
plt.figure()
99+
plt.plot(np.sort(centroidInfo[:, 0].flatten()))
100+
plt.title("Window Pre Centroid Intensities")
101+
plt.xlabel("Centroid #")
102+
plt.ylabel("Counts")
103+
if PLOT_SHOW:
104+
plt.show()
105+
106+
plt.figure()
107+
plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
108+
plt.title("Window Pre Centroid EOD")
109+
plt.xlabel("Centroid #")
110+
plt.ylabel("EOD (%)")
111+
if PLOT_SHOW:
112+
plt.show()
113+
114+
centroids = list(NumCpp.generateCentroids(cScene, thresholdRate, "post", borderWidth))
115+
print(f"Window Post Number of Centroids (Border = {borderWidth}) = {len(centroids)}")
116+
117+
# plt the results
118+
plt.figure()
119+
plt.imshow(scene)
120+
plt.colorbar()
121+
plt.clim([threshold, threshold + 1])
122+
plt.xlabel("Rows")
123+
plt.ylabel("Cols")
124+
plt.title(f"Window Post Centroids\nNumber of Centroids = {len(centroids)}")
125+
126+
for centroid in centroids:
127+
plt.plot(centroid.col(), centroid.row(), "og", fillstyle="none")
128+
129+
if PLOT_SHOW:
130+
plt.show()
131+
132+
centroidInfo = np.asarray([[centroid.intensity(), centroid.eod()] for centroid in centroids])
133+
134+
plt.figure()
135+
plt.plot(np.sort(centroidInfo[:, 0].flatten()))
136+
plt.title("Window Post Centroid Intensities")
137+
plt.xlabel("Centroid #")
138+
plt.ylabel("Counts")
139+
if PLOT_SHOW:
140+
plt.show()
141+
142+
plt.figure()
143+
plt.plot(np.sort(centroidInfo[:, 1].flatten() * 100))
144+
plt.title("Window Post Centroid EOD")
145+
plt.xlabel("Centroid #")
146+
plt.ylabel("EOD (%)")
147+
if PLOT_SHOW:
148+
plt.show()
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plt.close("all")

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