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UNI_Python
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08/01/2023

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Jan-Niclas Loosen 8 months ago
parent 8e3db2af40
commit 076f19cd27
8 changed files with 81 additions and 167 deletions
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11
.idea/UNI_Python.iml
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72
ha_08/loosen_janniclas_1540907_09.py
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@ -1,9 +1,10 @@
import colorsys import colorsys
import plotly.graph_objects as go from io import BytesIO
import requests
from PIL import Image from PIL import Image
import numpy as np import numpy as np
from matplotlib import pyplot as plt from matplotlib import pyplot as plt
import time
def apply_convolution_operator(operator, image): def apply_convolution_operator(operator, image):
@ -74,41 +75,41 @@ laplace = np.array([
[0, 1, 0] [0, 1, 0]
]) ])
""" sharp = np.array([
url = "https://cdn.prod.www.spiegel.de/images/9f9be1b3-ac0e-49f9-acbd-a809a102f9b6_w960_r1.778_fpx39_fpy30.jpg" [0, -1, 0],
[-1, 5, -1],
[0, -1, 0]
])
url = "https://media.newyorker.com/photos/5e3b18f932d7150008e6cf16/master/w_2240,c_limit/Neima-Picard.jpg"
response = requests.get(url) response = requests.get(url)
if response.status_code == 200: if response.status_code == 200:
# image = Image.open(BytesIO(response.content)) image = Image.open(BytesIO(response.content))
image = Image.open("next_generation.jpg") operators = [g1, g2, g3, g4]
operators = [laplace]
edited_image = image
for operator in operators: for operator in operators:
edited_image = apply_convolution_operator(operator, edited_image) image_edited = apply_convolution_operator(operator, image)
edited_image = edited_image.convert("RGB") # Convert to RGB mode image_edited.show()
edited_image.show()
edited_image.save("edited.jpg")
else: else:
print(f"Failed to download image. Status code: {response.status_code}") print(f"Failed to download image. Status code: {response.status_code}")
"""
class Heatmap_Simulator: class Heatmap_Simulator:
k = 1 k, h, delta_f = 1, 0.01, 0.05
h = 2 # Add more accurate cooling effect:
delta_f = 0.005 # tmp_min, tmp_max, env = -0.5, 1, -0.5
tmp_min, tmp_max, env = 0, 1, 0
cookie_size = 0.5 cookie_size = 0.5
def __init__(self, y_size=28, x_size=28, tmp_min=0, tmp_max=1): def __init__(self, y_size=28, x_size=28):
init_heatmap = np.zeros((y_size, x_size)) init_heatmap = np.full((y_size, x_size), self.tmp_min)
self.x_size = x_size self.x_size = x_size
self.y_size = y_size self.y_size = y_size
self.tmp_min = tmp_min
self.tmp_max = tmp_max
size = self.cookie_size / 2 size = self.cookie_size / 2
for y in range(int(y_size * (0.5 - size)), int(y_size * (0.5 + size))): for y in range(int(y_size * (0.5 - size)), int(y_size * (0.5 + size))):
for x in range(int(x_size * (0.5 - size)), int(x_size * (0.5 + size))): for x in range(int(x_size * (0.5 - size)), int(x_size * (0.5 + size))):
init_heatmap[y][x] = 1 init_heatmap[y][x] = self.tmp_max
self.heatmap = init_heatmap self.heatmap = init_heatmap
def simulate(self, cycles=1): def simulate(self, cycles=1):
@ -123,10 +124,10 @@ class Heatmap_Simulator:
self.heatmap = new_heatmap self.heatmap = new_heatmap
def _consider_convolution(self, x, y): def _consider_convolution(self, x, y):
top = self.heatmap[y - 1, x] if y > 0 else 0 top = self.heatmap[y - 1, x] if y > 0 else self.env
bottom = self.heatmap[y + 1, x] if y < self.heatmap.shape[0] - 1 else 0 bottom = self.heatmap[y + 1, x] if y < self.heatmap.shape[0] - 1 else self.env
left = self.heatmap[y, x - 1] if x > 0 else 0 left = self.heatmap[y, x - 1] if x > 0 else self.env
right = self.heatmap[y, x + 1] if x < self.heatmap.shape[1] - 1 else 0 right = self.heatmap[y, x + 1] if x < self.heatmap.shape[1] - 1 else self.env
center = self.heatmap[y, x] center = self.heatmap[y, x]
return top + bottom + left + right + center * (-4) return top + bottom + left + right + center * (-4)
@ -138,8 +139,8 @@ class Heatmap_Simulator:
class Visual_Heatmap_Simulator(Heatmap_Simulator): class Visual_Heatmap_Simulator(Heatmap_Simulator):
def __init__(self, y_size=28, x_size=28, tmp_min=0, tmp_max=1, delay=0.5): def __init__(self, y_size=28, x_size=28, delay=0.5):
super().__init__(y_size, x_size, tmp_min, tmp_max) super().__init__(y_size, x_size)
self.delay = delay self.delay = delay
def simulate_visual(self, cycles=100, skip=5): def simulate_visual(self, cycles=100, skip=5):
@ -151,15 +152,11 @@ class Visual_Heatmap_Simulator(Heatmap_Simulator):
print(f"Figure updated: {c}.") print(f"Figure updated: {c}.")
def _update_plot(self): def _update_plot(self):
plt.imshow(self.heatmap, cmap='viridis', interpolation='nearest') plt.imshow(self.heatmap, cmap='viridis', interpolation='nearest', vmin=self.tmp_min, vmax=self.tmp_max)
plt.draw() plt.draw()
plt.pause(self.delay) plt.pause(self.delay)
simulator = Visual_Heatmap_Simulator(28, 28, -0.5, 1)
simulator.simulate_visual(10000, 50)
class Heatmap_Image: class Heatmap_Image:
def __init__(self, heatmap, min_val, max_val): def __init__(self, heatmap, min_val, max_val):
self.min_val = min_val self.min_val = min_val
@ -183,3 +180,14 @@ class Heatmap_Image:
def save(self, file): def save(self, file):
self.image.save(file) self.image.save(file)
"""
sim = Heatmap_Simulator()
img = sim.export()
img.save("img_0.jpg")
for i in range(1,20):
sim.simulate(100)
img = sim.export()
img.save(f"img_{i}.jpg")
"""

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