def get_gray_scal(self, image_file):
image = loadRGB(image_file)
som1D, som2D = self.setupSOM(image)
print(" - Train 2D")
som2D.trainAll()
som2D_plot = SOMPlot(som2D)
gray, gray_reverse = som2D_plot.showGrayImage2(image)
return gray, gray_reverse
def singleImageResult(image_file):
image_name = os.path.basename(image_file)
image_name = os.path.splitext(image_name)[0]
image = loadRGB(image_file)
som1D, som2D = setupSOM(image)
fig = plt.figure(figsize=(10, 7))
fig.subplots_adjust(left=0.05, bottom=0.05, right=0.95, top=0.9, wspace=0.1, hspace=0.2)
font_size = 15
fig.suptitle("SOM-Color Manifolds for Single Image", fontsize=font_size)
plt.subplot(231)
h, w = image.shape[:2]
plt.title("Original Image: %s x %s" % (w, h), fontsize=font_size)
plt.imshow(image)
plt.axis('off')
print " - Train 1D"
som1D.trainAll()
print " - Train 2D"
som2D.trainAll()
som1D_plot = SOMPlot(som1D)
som2D_plot = SOMPlot(som2D)
plt.subplot(232)
plt.title("SOM 1D", fontsize=font_size)
som1D_plot.updateImage()
plt.axis('off')
plt.subplot(233)
plt.title("SOM 2D", fontsize=font_size)
som2D_plot.updateImage()
plt.axis('off')
ax1D = fig.add_subplot(235, projection='3d')
plt.title("1D in 3D", fontsize=font_size)
som1D_plot.plot3D(ax1D)
ax2D = fig.add_subplot(236, projection='3d')
plt.title("2D in 3D", fontsize=font_size)
som2D_plot.plot3D(ax2D)
result_file = resultFile("%s_single" % image_name)
plt.savefig(result_file)
def animationResultImp(image_file):
image_name = os.path.basename(image_file)
image_name = os.path.splitext(image_name)[0]
image = loadRGB(image_file)
som1D, som2D = setupSOM(image)
fig = plt.figure()
fig.subplots_adjust(left=0.05,
bottom=0.05,
right=0.95,
top=0.9,
wspace=0.1,
hspace=0.2)
font_size = 15
fig.suptitle("SOM-Color Manifolds (Animation)", fontsize=font_size)
plt.subplot(131)
plt.title("%s" % (image_name))
plt.imshow(image)
plt.axis('off')
plt.subplot(132)
plt.title("SOM 1D")
som1D_plot = SOMPlot(som1D)
ani1D = animation.FuncAnimation(fig,
som1D_plot.trainAnimation,
interval=0,
blit=True)
plt.axis('off')
plt.subplot(133)
plt.title("SOM 2D")
som2D_plot = SOMPlot(som2D)
ani2D = animation.FuncAnimation(fig,
som2D_plot.trainAnimation,
interval=0,
blit=True)
plt.axis('off')
showMaximize()
def color_to_gray_debug(self, image_file, gray_name, gray_reverse_name,
debug):
image = loadRGB(image_file)
som1D, som2D = self.setupSOM(image)
fig = plt.figure(figsize=(12, 10))
fig.subplots_adjust(left=0.05,
bottom=0.05,
right=0.95,
top=0.9,
wspace=0.1,
hspace=0.2)
font_size = 15
fig.suptitle("SOM-Color Manifolds for Single Image",
fontsize=font_size)
plt.subplot(331)
h, w = image.shape[:2]
plt.title("Original Image: %s x %s" % (w, h), fontsize=font_size)
plt.imshow(image)
plt.axis('off')
print(" - Train 1D")
som1D.trainAll()
print(" - Train 2D")
som2D.trainAll()
som1D_plot = SOMPlot(som1D)
som2D_plot = SOMPlot(som2D)
plt.subplot(332)
plt.title("SOM 1D", fontsize=font_size)
# 如果改变updateImage函数的返回值，那么可以用以下语句，代替以下第二行语句。
# plt.imshow(som1D_plot.updateImage())
som1D_plot.updateImage()
plt.axis('off')
plt.subplot(333)
plt.title("SOM 2D", fontsize=font_size)
som2D_plot.updateImage()
plt.axis('off')
color_pixels = ColorPixels(image)
pixels = color_pixels.pixels(color_space="rgb")
ax = fig.add_subplot(334, projection='3d')
plt.title("cloudPoint", fontsize=font_size)
som1D_plot.plotCloud(ax, pixels)
hist3D = Hist3D(image, num_bins=16)
color_samples = hist3D.colorCoordinates()
ax = fig.add_subplot(337, projection='3d')
plt.title("cloudPoint", fontsize=font_size)
som1D_plot.plotCloud(ax, color_samples)
ax1D = fig.add_subplot(335, projection='3d')
plt.title("1D in 3D", fontsize=font_size)
som1D_plot.plot3D(ax1D)
ax2D = fig.add_subplot(336, projection='3d')
plt.title("2D in 3D", fontsize=font_size)
som2D_plot.plot3D(ax2D)
plt.subplot(338)
plt.title("Gray", fontsize=font_size)
# 如果改变updateImage函数的返回值，那么可以用以下语句，代替以下第二行语句。
a, b = som2D_plot.showGrayImage2(image)
plt.imshow(a, cmap='gray', vmin=0, vmax=1)
plt.axis('off')
plt.imsave(self.resultFile(gray_name), a, cmap='gray', vmin=0, vmax=1)
plt.imsave(self.resultFile(gray_reverse_name),
b,
cmap='gray',
vmin=0,
vmax=1)
plt.subplot(339)
plt.title("Gray", fontsize=font_size)
plt.imshow(b, cmap='gray', vmin=0, vmax=1)
plt.axis('off')
result_file = self.resultFile("%s_debug" % gray_name)
plt.savefig(result_file)
def multiImagesResult(data_name, data_ids):
num_cols = len(data_ids)
num_rows = 2
fig = plt.figure(figsize=(12, 6))
fig.subplots_adjust(left=0.05,
bottom=0.05,
right=0.95,
top=0.9,
wspace=0.1,
hspace=0.2)
font_size = 15
fig.suptitle("SOM-Color Manifolds for Multi Images", fontsize=font_size)
color_samples = []
col_id = 0
for data_id in data_ids:
image_file = dataFile(data_name, data_id)
image_name = "%s_%s" % (data_name, data_id + 1)
image = loadRGB(image_file)
hist3D = Hist3D(image, num_bins=16)
color_samples.extend(hist3D.colorCoordinates())
plt.subplot2grid((num_rows, num_cols), (0, col_id))
plt.title("%s" % image_name, fontsize=font_size)
plt.imshow(image)
plt.axis('off')
col_id += 1
color_samples = np.array(color_samples)
print color_samples.shape
som1D, som2D = setupSOM(color_samples)
print " - Train 1D"
som1D.trainAll()
print " - Train 2D"
som2D.trainAll()
som1D_plot = SOMPlot(som1D)
som2D_plot = SOMPlot(som2D)
col_id = 1
plt.subplot2grid((num_rows, num_cols), (1, col_id))
plt.title("SOM 1D", fontsize=font_size)
som1D_plot.updateImage()
plt.axis('off')
col_id += 1
ax1D = plt.subplot2grid((num_rows, num_cols), (1, col_id),
projection='3d',
aspect='equal')
plt.title("1D in 3D", fontsize=font_size)
som1D_plot.plot3D(ax1D)
col_id += 1
plt.subplot2grid((num_rows, num_cols), (1, col_id))
plt.title("SOM 2D", fontsize=font_size)
som2D_plot.updateImage()
plt.axis('off')
col_id += 1
ax2D = plt.subplot2grid((num_rows, num_cols), (1, col_id),
projection='3d',
aspect='equal')
plt.title("2D in 3D", fontsize=font_size)
som2D_plot.plot3D(ax2D)
result_file = resultFile("%s_multi" % data_name)
plt.savefig(result_file)
def singleImageResult(image_file):
print image_file
image_name = os.path.basename(image_file)
image_name = os.path.splitext(image_name)[0]
image = loadRGB(image_file)
import time
start = time.time()
som1D, som2D = setupSOM(image)
fig = plt.figure(figsize=(12, 10))
fig.subplots_adjust(left=0.05, bottom=0.05, right=0.95, top=0.9, wspace=0.1, hspace=0.2)
print time.time() - start
font_size = 15
fig.suptitle("SOM-Color Manifolds for Single Image", fontsize=font_size)
plt.subplot(331)
h, w = image.shape[:2]
plt.title("Original Image: %s x %s" % (w, h), fontsize=font_size)
plt.imshow(image)
plt.axis('off')
print " - Train 1D"
som1D.trainAll()
print " - Train 2D"
som2D.trainAll()
som1D_plot = SOMPlot(som1D)
som2D_plot = SOMPlot(som2D)
plt.subplot(332)
plt.title("SOM 1D", fontsize=font_size)
# 如果改变updateImage函数的返回值，那么可以用以下语句，代替以下第二行语句。
# plt.imshow(som1D_plot.updateImage())
som1D_plot.updateImage()
plt.axis('off')
plt.subplot(333)
plt.title("SOM 2D", fontsize=font_size)
som2D_plot.updateImage()
plt.axis('off')
color_pixels = ColorPixels(image)
pixels = color_pixels.pixels(color_space="rgb")
ax = fig.add_subplot(334, projection='3d')
plt.title("cloudPoint", fontsize=font_size)
som1D_plot.plotCloud(ax, pixels)
hist3D = Hist3D(image, num_bins=16)
color_samples = hist3D.colorCoordinates()
ax = fig.add_subplot(337, projection='3d')
plt.title("cloudPoint", fontsize=font_size)
som1D_plot.plotCloud(ax, color_samples)
ax1D = fig.add_subplot(335, projection='3d')
plt.title("1D in 3D", fontsize=font_size)
som1D_plot.plot3D(ax1D)
ax2D = fig.add_subplot(336, projection='3d')
plt.title("2D in 3D", fontsize=font_size)
som2D_plot.plot3D(ax2D)
plt.subplot(338)
plt.title("Gray", fontsize=font_size)
# 如果改变updateImage函数的返回值，那么可以用以下语句，代替以下第二行语句。
a,b = som2D_plot.showGrayImage2(image)
plt.imshow(a, cmap='gray', vmin = 0, vmax = 1)
plt.axis('off')
plt.imsave('''./''' + image_name + '''.png''', a, cmap='gray',vmin = 0, vmax = 1)
plt.imsave('''./''' + image_name + '''!.png''', b, cmap='gray',vmin = 0, vmax = 1)
plt.subplot(339)
plt.title("Gray", fontsize=font_size)
plt.imshow(b, cmap='gray', vmin = 0, vmax = 1)
plt.axis('off')
result_file = resultFile("%s_single" % image_name)
plt.savefig(result_file)
def singleImageResult(image_file):
image_name = os.path.basename(image_file)
image_name = os.path.splitext(image_name)[0]
image = loadRGB(image_file)
som1D, som2D = setupSOM(image)
fig = plt.figure(figsize=(10, 7))
fig.subplots_adjust(left=0.05,
bottom=0.05,
right=0.95,
top=0.9,
wspace=0.1,
hspace=0.2)
font_size = 15
fig.suptitle("SOM-Color Manifolds for Single Image", fontsize=font_size)
plt.subplot(231)
h, w = image.shape[:2]
plt.title("Original Image: %s x %s" % (w, h), fontsize=font_size)
plt.imshow(image)
plt.axis('off')
print " - Train 1D"
som1D.trainAll()
print " - Train 2D"
som2D.trainAll()
som1D_plot = SOMPlot(som1D)
som2D_plot = SOMPlot(som2D)
plt.subplot(232)
plt.title("SOM 1D", fontsize=font_size)
som1D_plot.updateImage()
plt.axis('off')
plt.subplot(233)
plt.title("SOM 2D", fontsize=font_size)
som2D_plot.updateImage()
plt.axis('off')
ax1D = fig.add_subplot(235, projection='3d')
plt.title("1D in 3D", fontsize=font_size)
som1D_plot.plot3D(ax1D)
ax2D = fig.add_subplot(236, projection='3d')
plt.title("2D in 3D", fontsize=font_size)
som2D_plot.plot3D(ax2D)
result_file = resultFile("%s_single" % image_name)
plt.savefig(result_file)
