def process(image, model, debug=None):
"""
This function processes an image given a model, and returns a list of Box.
"""
debug_inner = debug in ["inner", "all"]
contours = get_box_contours(image, debug=debug_inner)
sprites = get_sprites(image, contours, debug=debug_inner)
inputs = preprocess_sprites(sprites, debug=debug_inner)
labels = [model.infer(i) for i in inputs]
boxes = [
Box(contour=c, sprite=s, label=l)
for c, s, l in zip(contours, sprites, labels)
]
if debug in ["all", "synthesis"]:
for box in boxes:
fig, ax = plt.subplots(nrows=2)
ax[0].imshow(image)
ax[0].plot(box.contour[:, 0], box.contour[:, 1], "og")
ax[0].plot(
box.contour.mean(axis=0)[0],
box.contour.mean(axis=0)[1], "og")
ax[1].imshow(box.sprite)
ax[1].set_title("Label recognized: {}".format(box.label))
plt.show()
return boxes
def process(image, model, debug=None):
"""
This function processes an image given a model, and returns a list of Box.
"""
debug_inner = debug in ["inner", "all"]
contours = get_box_contours(image, debug=debug_inner)
sprites = get_sprites(image, contours, debug=debug_inner)
inputs = preprocess_sprites(sprites, debug=debug_inner)
labels = [
model.predict(i.reshape(1, 28, 28, 1)).squeeze().argmax() + 1
for i in inputs
]
boxes = [
Box(contour=c, sprite=s, input=i, label=l)
for c, s, i, l in zip(contours, sprites, inputs, labels)
]
if debug in ["all", "synthesis"]:
for box in boxes:
fig, ax = plt.subplots(nrows=2)
ax[0].imshow(image, cmap='gray')
ax[0].plot(box.contour[:, 0], box.contour[:, 1], "og")
ax[0].plot(
box.contour.mean(axis=0)[0],
box.contour.mean(axis=0)[1], "og")
ax[0].set_axis_off()
ax[1].imshow(box.sprite, cmap='gray')
ax[1].imshow(box.input, cmap='gray')
ax[1].set_title("Label recognized: {}".format(box.label))
ax[1].set_axis_off()
plt.tight_layout()
plt.show()
return boxes