def test_read_write_png_noc(self):
input_filepath = "static/kitti_noc_000010_10.png"
flow = flowpy.flow_read(input_filepath)
_, output_filename = tempfile.mkstemp(suffix=".png")
try:
flowpy.flow_write(output_filename, flow)
new_flow = flowpy.flow_read(output_filename)
np.testing.assert_equal(new_flow, flow)
finally:
os.remove(output_filename)
def test_read_write_flo(self):
input_filepath = "static/Dimetrodon.flo"
flow = flowpy.flow_read(input_filepath)
with tempfile.NamedTemporaryFile("wb", suffix=".flo") as f:
flowpy.flow_write(f, flow)
self.assertTrue(filecmp.cmp(f.name, input_filepath))
def test_flow_with_arrows(self):
flow = flowpy.flow_read("static/kitti_occ_000010_10.png")
fig, ax = plt.subplots()
ax.imshow(flowpy.flow_to_rgb(flow))
flowpy.attach_arrows(ax, flow, xy_steps=(20, 20), scale=1)
plt.show()
def test_flow_arrows_and_coord(self):
flow = flowpy.flow_read("static/Dimetrodon.flo")
fig, ax = plt.subplots()
ax.imshow(flowpy.flow_to_rgb(flow))
flowpy.attach_arrows(ax, flow)
flowpy.attach_coord(ax, flow)
plt.show()
def test_forward_warp_rgb(self):
flow = flowpy.flow_read("static/kitti_occ_000010_10.png")
first_image = np.asarray(Image.open("static/kitti_000010_10.png"))
second_image = np.asarray(Image.open("static/kitti_000010_11.png"))
flow[np.isnan(flow)] = 0
warped_second_image = flowpy.forward_warp(first_image, flow, k=1)
fig, (ax_1, ax_2, ax_3) = plt.subplots(3, 1)
ax_1.imshow(first_image)
ax_2.imshow(flowpy.flow_to_rgb(flow))
ax_3.imshow(warped_second_image)
plt.show()
def test_backward_warp_greyscale(self):
flow = flowpy.flow_read("static/kitti_occ_000010_10.png")
first_image = np.asarray(
Image.open("static/kitti_000010_10.png").convert("L"))
second_image = np.asarray(
Image.open("static/kitti_000010_11.png").convert("L"))
flow[np.isnan(flow)] = 0
warped_first_image = flowpy.backward_warp(second_image, flow)
fig, (ax_1, ax_2, ax_3) = plt.subplots(3, 1)
ax_1.imshow(first_image)
ax_2.imshow(second_image)
ax_3.imshow(warped_first_image)
plt.show()
def test_flow_arrows_coord_and_calibration_pattern(self):
flow = flowpy.flow_read("static/Dimetrodon.flo")
height, width, _ = flow.shape
image_ratio = height / width
max_radius = flowpy.get_flow_max_radius(flow)
fig, (ax_1, ax_2) = plt.subplots(
1, 2, gridspec_kw={"width_ratios": [1, image_ratio]})
ax_1.imshow(flowpy.flow_to_rgb(flow))
flowpy.attach_arrows(ax_1, flow)
flowpy.attach_coord(ax_1, flow)
flowpy.attach_calibration_pattern(ax_2, flow_max_radius=max_radius)
plt.show()
def test_flow_to_rgb(self):
flow = flowpy.flow_read("static/Dimetrodon.flo")
plt.imshow(flowpy.flow_to_rgb(flow))
plt.show()
.png (as defined here)
Visualizing optical flows with matplotlib
Backward and forward warp
"""
# Examples a simple RGB plot
"""
This is the simplest example of how to use flowpy, it:
Reads a file using flowpy.flow_read.
Transforms the flow as an rgb image with flowpy.flow_to_rgb and shows it with matplotlib
"""
import flowpy
import matplotlib.pyplot as plt
flow = flowpy.flow_read("tests/data/kitti_occ_000010_10.flo")
fig, ax = plt.subplots()
ax.imshow(flowpy.flow_to_rgb(flow))
plt.show()
# Plotting arrows, showing flow values and a calibration pattern
# Flowpy comes with more than just RGB plots, the main features here are: - Arrows to quickly visualize the flow -
# The flow values below cursor showing in the tooltips - A calibration pattern side by side as a legend for your graph
flow = flowpy.flow_read("tests/data/Dimetrodon.flo")
height, width, _ = flow.shape
image_ratio = height / width
max_radius = flowpy.get_flow_max_radius(flow)
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
import flowpy
flow = flowpy.flow_read("static/kitti_occ_000010_10.png")
first_image = np.asarray(Image.open("static/kitti_000010_10.png"))
second_image = np.asarray(Image.open("static/kitti_000010_11.png"))
flow[np.isnan(flow)] = 0
warped_first_image = flowpy.backward_warp(second_image, flow)
fig, axes = plt.subplots(3, 1)
for ax, image, title in zip(
axes, (first_image, second_image, warped_first_image),
("First Image", "Second Image", "Second image warped to first image")):
ax.imshow(image)
ax.set_title(title)
ax.set_axis_off()
plt.show()
import flowpy
import matplotlib.pyplot as plt
flow = flowpy.flow_read("static/Dimetrodon.flo")
height, width, _ = flow.shape
image_ratio = height / width
max_radius = flowpy.get_flow_max_radius(flow)
fig, (ax_1,
ax_2) = plt.subplots(1,
2,
gridspec_kw={"width_ratios": [1, image_ratio]})
ax_1.imshow(flowpy.flow_to_rgb(flow))
flowpy.attach_arrows(ax_1, flow)
flowpy.attach_coord(ax_1, flow)
flowpy.attach_calibration_pattern(ax_2, flow_max_radius=max_radius)
plt.show()