def render_label_pred_example():
model_path = path_model2d()
model = StarDist2D(None,
name=model_path.name,
basedir=str(model_path.parent))
img, y_gt = real_image2d()
x = normalize(img, 1, 99.8)
y, _ = model.predict_instances(x)
im = render_label_pred(y_gt, y, img=x)
import matplotlib.pyplot as plt
plt.figure(1, figsize=(12, 4))
plt.subplot(1, 4, 1)
plt.imshow(x)
plt.title("img")
plt.subplot(1, 4, 2)
plt.imshow(render_label(y_gt, img=x))
plt.title("gt")
plt.subplot(1, 4, 3)
plt.imshow(render_label(y, img=x))
plt.title("pred")
plt.subplot(1, 4, 4)
plt.imshow(im)
plt.title("tp (green) fp (red) fn(blue)")
plt.tight_layout()
plt.show()
return im
def render_label_pred_example(model2d):
model = model2d
img, y_gt = real_image2d()
x = normalize(img, 1, 99.8)
y, _ = model.predict_instances(x)
im = render_label_pred(y_gt, y , img = x)
import matplotlib.pyplot as plt
plt.figure(1, figsize = (12,4))
plt.subplot(1,4,1);plt.imshow(x);plt.title("img")
plt.subplot(1,4,2);plt.imshow(render_label(y_gt, img = x));plt.title("gt")
plt.subplot(1,4,3);plt.imshow(render_label(y, img = x));plt.title("pred")
plt.subplot(1,4,4);plt.imshow(im);plt.title("tp (green) fp (red) fn(blue)")
plt.tight_layout()
plt.show()
return im
def render_label_example(model2d):
model = model2d
img, y_gt = real_image2d()
x = normalize(img, 1, 99.8)
y, _ = model.predict_instances(x)
# im = render_label(y,img = x, alpha = 0.3, alpha_boundary=1, cmap = (.3,.4,0))
im = render_label(y,img = x, alpha = 0.3, alpha_boundary=1)
import matplotlib.pyplot as plt
plt.figure(1)
plt.imshow(im)
plt.show()
return im
def render_label_example():
model_path = path_model2d()
model = StarDist2D(None,
name=model_path.name,
basedir=str(model_path.parent))
img, y_gt = real_image2d()
x = normalize(img, 1, 99.8)
y, _ = model.predict_instances(x)
# im = render_label(y,img = x, alpha = 0.3, alpha_boundary=1, cmap = (.3,.4,0))
im = render_label(y, img=x, alpha=0.3, alpha_boundary=1)
import matplotlib.pyplot as plt
plt.figure(1)
plt.imshow(im)
plt.show()
return im