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Update myturtle_cv.py
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import numpy as np
import cv2
def crop_and_scaled_imgs(imgs):
PAD = 5
# use the last image to find the bounding box of the non-white area and the transformation parameters
# and then apply the transformation to all images
img = imgs[-1]
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Threshold the image to create a binary mask
_, binary_mask = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)
# Find the coordinates of non-zero pixels
coords = cv2.findNonZero(binary_mask)
# Get the bounding box of the non-zero pixels
x, y, w, h = cv2.boundingRect(coords)
x = max(0, x-PAD)
y = max(0, y-PAD)
x_end = min(img.shape[1], x+w+2*PAD)
y_end = min(img.shape[0], y+h+2*PAD)
w = x_end - x
h = y_end - y
SIZE = 400
# Calculate the position to center the ROI in the SIZExSIZE image
start_x = max(0, (SIZE - w) // 2)
start_y = max(0, (SIZE - h) // 2)
# Create a new SIZExSIZE rgb images
new_imgs = [np.ones((SIZE, SIZE, 3), dtype=np.uint8) * 255 for _ in range(len(imgs))]
for i in range(len(imgs)):
# Extract the ROI (region of interest) of the non-white area
roi = imgs[i][y:y+h, x:x+w]
# If the ROI is larger than 256x256, resize it
if w > SIZE or h > SIZE:
scale = min(SIZE / w, SIZE / h)
new_w = int(w * scale)
new_h = int(h * scale)
roi = cv2.resize(roi, (new_w, new_h), interpolation=cv2.INTER_AREA)
else:
new_w = w
new_h = h
# new_imgs[i] = np.ones((256, 256), dtype=np.uint8) * 255
# centered_img = np.ones((256, 256), dtype=np.uint8) * 255
# Place the ROI in the centered position
new_imgs[i][start_y:start_y+new_h, start_x:start_x+new_w] = roi
return new_imgs
HALF_INF = 63
INF = 126
EPS_DIST = 1/20
EPS_ANGLE = 2.86
SCALE = 15
MOVE_SPEED = 25
ROTATE_SPEED = 30
FPS = 24
class Turtle:
def __init__(self, canvas_size=(2000, 2000)):
self.x = canvas_size[0] // 2
self.y = canvas_size[1] // 2
self.heading = 0
self.canvas = np.ones((canvas_size[1], canvas_size[0], 3), dtype=np.uint8) * 255
self.is_down = True
self.time_since_last_frame = 0
self.frames = [self.canvas.copy()]
def forward(self, dist):
# print('st', self.x, self.y)
# self.forward_step(dist * SCALE)
# print('ed', self.x, self.y)
# return
dist = dist * SCALE
sign = 1 if dist > 0 else -1
abs_dist = abs(dist)
if self.time_since_last_frame + abs_dist / MOVE_SPEED >= 1:
dist1 = (1 - self.time_since_last_frame) * MOVE_SPEED
self.forward_step(dist1 * sign)
self.save_frame_with_turtle()
self.time_since_last_frame = 0
# for loop to step forward
num_steps = int((abs_dist - dist1) / MOVE_SPEED)
for _ in range(num_steps):
self.forward_step(MOVE_SPEED * sign)
self.save_frame_with_turtle()
last_abs_dist = abs_dist - dist1 - num_steps * MOVE_SPEED
if last_abs_dist >= MOVE_SPEED:
self.forward_step(MOVE_SPEED * sign)
self.save_frame_with_turtle()
last_abs_dist -= MOVE_SPEED
self.forward_step(last_abs_dist * sign)
self.time_since_last_frame = last_abs_dist / MOVE_SPEED
else:
self.forward_step(abs_dist * sign)
# self.time_since_last_frame += abs_dist / MOVE_SPEED
# if self.time_since_last_frame >= 1:
# self.time_since_last_frame = 0
def forward_step(self, dist):
# print('step', dist)
if dist == 0:
return
x0, y0 = self.x, self.y
x1 = (x0 + dist * np.cos(self.heading))
y1 = (y0 - dist * np.sin(self.heading))
if self.is_down:
cv2.line(self.canvas, (int(np.rint(x0)), int(np.rint(y0))), (int(np.rint(x1)), int(np.rint(y1))), (0, 0, 0), 3)
self.x, self.y = x1, y1
self.time_since_last_frame += abs(dist) / MOVE_SPEED
# self.frames.append(self.canvas.copy())
# self.save_frame_with_turtle()
# print(self.x, self.y)
def save_frame_with_turtle(self):
# save the current frame to frames buffer
# also plot a red triangle to represent the turtle pointing to the current direction
# draw the turtle
x, y = self.x, self.y
canvas_copy = self.canvas.copy()
triangle_size = 10
x0 = int(np.rint(x + triangle_size * np.cos(self.heading)))
y0 = int(np.rint(y - triangle_size * np.sin(self.heading)))
x1 = int(np.rint(x + triangle_size * np.cos(self.heading + 2 * np.pi / 3)))
y1 = int(np.rint(y - triangle_size * np.sin(self.heading + 2 * np.pi / 3)))
x2 = int(np.rint(x + triangle_size * np.cos(self.heading - 2 * np.pi / 3)))
y2 = int(np.rint(y - triangle_size * np.sin(self.heading - 2 * np.pi / 3)))
x3 = int(np.rint(x - 0.25 * triangle_size * np.cos(self.heading)))
y3 = int(np.rint(y + 0.25 * triangle_size * np.sin(self.heading)))
# fill the triangle
cv2.fillPoly(canvas_copy, [np.array([(x0, y0), (x1, y1), (x3, y3), (x2, y2)], dtype=np.int32)], (0, 0, 255))
self.frames.append(canvas_copy)
def left(self, angle):
# print('angel', angle)
# print('ast', self.heading)
# self.heading += angle * np.pi / 180
self.turn_to(angle)
# print('aed', self.heading)
def right(self, angle):
# print('angel', angle)
# print('ast', self.heading)
# self.heading -= angle * np.pi / 180
self.turn_to(-angle)
# print('aed', self.heading)
def turn_to(self, angle):
abs_angle = abs(angle)
sign = 1 if angle > 0 else -1
if self.time_since_last_frame + abs(angle) / ROTATE_SPEED > 1:
angle1 = (1 - self.time_since_last_frame) * ROTATE_SPEED
self.turn_to_step(angle1 * sign)
self.save_frame_with_turtle()
self.time_since_last_frame = 0
num_steps = int((abs_angle - angle1) / ROTATE_SPEED)
for _ in range(num_steps):
self.turn_to_step(ROTATE_SPEED * sign)
self.save_frame_with_turtle()
last_abs_angle = abs_angle - angle1 - num_steps * ROTATE_SPEED
if last_abs_angle >= ROTATE_SPEED:
self.turn_to_step(ROTATE_SPEED * sign)
self.save_frame_with_turtle()
last_abs_angle -= ROTATE_SPEED
self.turn_to_step(last_abs_angle * sign)
self.time_since_last_frame = last_abs_angle / ROTATE_SPEED
else:
self.turn_to_step(abs_angle * sign)
# self.time_since_last_frame += abs_angle / ROTATE_SPEED
def turn_to_step(self, angle):
# print('turn step', angle)
self.heading += angle * np.pi / 180
self.time_since_last_frame += abs(angle) / ROTATE_SPEED
def penup(self):
self.is_down = False
def pendown(self):
self.is_down = True
def save(self, path):
if path:
cv2.imwrite(path, self.canvas)
return self.canvas
def save_gif(self, path):
import imageio.v3 as iio
frames_rgb = [cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) for frame in self.frames]
print(f'number of frames: {len(frames_rgb)}')
frames_rgb.extend(FPS*2 * [frames_rgb[-1]])
frames_rgb = crop_and_scaled_imgs(frames_rgb)
# iio.imwrite(path, np.stack(frames_rgb), fps=30, plugin='pillow')
return iio.imwrite('<bytes>', np.stack(frames_rgb), fps=FPS, loop=0, plugin='pillow', format='gif')
class _TurtleState:
def __init__(self, turtle):
self.turtle = turtle
self.position = None
self.heading = None
self.pen_status = None
def __enter__(self):
self.position = (self.turtle.x, self.turtle.y)
self.heading = self.turtle.heading
self.pen_status = self.turtle.is_down
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.turtle.penup()
self.turtle.x, self.turtle.y = self.position
self.turtle.heading = self.heading
if self.pen_status:
self.turtle.pendown()
if __name__ == "__main__":
turtle = Turtle()
def forward(dist):
turtle.forward(dist)
def left(angle):
turtle.left(angle)
def right(angle):
turtle.right(angle)
def penup():
turtle.penup()
def pendown():
turtle.pendown()
def save(path):
turtle.save(path)
def fork_state():
"""
Clone the current state of the turtle.
Usage:
with clone_state():
forward(100)
left(90)
forward(100)
"""
return turtle._TurtleState(turtle)
# Example usage
def example_plot():
forward(5)
with fork_state():
forward(10)
left(90)
forward(10)
with fork_state():
right(90)
forward(20)
left(90)
forward(10)
left(90)
forward(10)
right(90)
forward(50)
save("test2.png")
return turtle.frames
def plot2():
for j in range(2):
forward(2)
left(0.0)
for i in range(4):
forward(2)
left(90)
forward(0)
left(180.0)
forward(2)
left(180.0)
FINAL_IMAGE = turtle.save("")
def plot3():
frames = []
frames.append(np.array(turtle.save("")))
for j in range(2):
forward(2)
frames.append(np.array(turtle.save("")))
left(0.0)
for i in range(4):
forward(2)
left(90)
frames.append(np.array(turtle.save("")))
forward(0)
left(180.0)
forward(2)
left(180.0)
frames.append(np.array(turtle.save("")))
return frames
def make_gif(frames, filename):
import imageio
frames_rgb = [cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) for frame in frames]
imageio.mimsave(filename, frames_rgb, fps=30)
def make_gif2(frames, filename):
import imageio.v3 as iio
frames_rgb = [cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) for frame in frames]
print(f'number of frames: {len(frames_rgb)}')
iio.imwrite(filename, np.stack(frames_rgb), fps=30, plugin='pillow')
def make_gif3(frames, filename):
from moviepy.editor import ImageSequenceClip
clip = ImageSequenceClip(list(frames), fps=20)
clip.write_gif(filename, fps=20)
def make_gif4(frames, filename):
from array2gif import write_gif
write_gif(frames, filename, fps=20)
def make_gif5(frames, filename):
from PIL import Image
frames_rgb = [cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) for frame in frames]
images = [Image.fromarray(frame) for frame in frames_rgb]
images[0].save(filename, save_all=True, append_images=images[1:], duration=100, loop=0)
def plot4():
# the following program draws a treelike pattern
import random
def draw_tree(level, length, angle):
if level == 0:
return
else:
forward(length)
left(angle)
draw_tree(level-1, length*0.7, angle*0.8)
right(angle*2)
draw_tree(level-1, length*0.7, angle*0.8)
left(angle)
forward(-length)
random.seed(0) # Comment this line to change the randomness
for _ in range(7): # Adjust the number to control the density
draw_tree(5, 5, 30)
forward(0)
left(random.randint(0, 360))
turtle.save("test3.png")
return turtle.frames
def plot5():
for i in range(7):
with fork_state():
for j in range(4):
forward(3*i)
left(90.0)
return turtle.frames
# make_gif2(plot5(), "test.gif")
frames = plot5()
# frames = [cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) for frame in frames]
# breakpoint()
# from moviepy.editor import ImageClip, concatenate_videoclips
# clips = [ImageClip(frame).set_duration(1/24) for frame in frames]
# concat_clip = concatenate_videoclips(clips, method="compose")
# concat_clip.write_videofile("test.mp4", fps=24)
img_bytes_string = turtle.save_gif("")
# turtle.save('test3.png')
with open("test5.gif", "wb") as f:
f.write(img_bytes_string)
# example_plot()
# plot2()