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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
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72
ha_08/loosen_janniclas_1540907_09.py
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@ -1,9 +1,10 @@
import colorsys
import plotly.graph_objects as go
from io import BytesIO
import requests
from PIL import Image
import numpy as np
from matplotlib import pyplot as plt
import time
def apply_convolution_operator(operator, image):
@ -74,41 +75,41 @@ laplace = np.array([
[0, 1, 0]
])
"""
url = "https://cdn.prod.www.spiegel.de/images/9f9be1b3-ac0e-49f9-acbd-a809a102f9b6_w960_r1.778_fpx39_fpy30.jpg"
sharp = np.array([
[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)
if response.status_code == 200:
# image = Image.open(BytesIO(response.content))
image = Image.open("next_generation.jpg")
operators = [laplace]
edited_image = image
image = Image.open(BytesIO(response.content))
operators = [g1, g2, g3, g4]
for operator in operators:
edited_image = apply_convolution_operator(operator, edited_image)
edited_image = edited_image.convert("RGB") # Convert to RGB mode
edited_image.show()
edited_image.save("edited.jpg")
image_edited = apply_convolution_operator(operator, image)
image_edited.show()
else:
print(f"Failed to download image. Status code: {response.status_code}")
"""
class Heatmap_Simulator:
k = 1
h = 2
delta_f = 0.005
k, h, delta_f = 1, 0.01, 0.05
# Add more accurate cooling effect:
# tmp_min, tmp_max, env = -0.5, 1, -0.5
tmp_min, tmp_max, env = 0, 1, 0
cookie_size = 0.5
def __init__(self, y_size=28, x_size=28, tmp_min=0, tmp_max=1):
init_heatmap = np.zeros((y_size, x_size))
def __init__(self, y_size=28, x_size=28):
init_heatmap = np.full((y_size, x_size), self.tmp_min)
self.x_size = x_size
self.y_size = y_size
self.tmp_min = tmp_min
self.tmp_max = tmp_max
size = self.cookie_size / 2
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))):
init_heatmap[y][x] = 1
init_heatmap[y][x] = self.tmp_max
self.heatmap = init_heatmap
def simulate(self, cycles=1):
@ -123,10 +124,10 @@ class Heatmap_Simulator:
self.heatmap = new_heatmap
def _consider_convolution(self, x, y):
top = self.heatmap[y - 1, x] if y > 0 else 0
bottom = self.heatmap[y + 1, x] if y < self.heatmap.shape[0] - 1 else 0
left = self.heatmap[y, x - 1] if x > 0 else 0
right = self.heatmap[y, x + 1] if x < self.heatmap.shape[1] - 1 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 self.env
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 self.env
center = self.heatmap[y, x]
return top + bottom + left + right + center * (-4)
@ -138,8 +139,8 @@ class 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):
super().__init__(y_size, x_size, tmp_min, tmp_max)
def __init__(self, y_size=28, x_size=28, delay=0.5):
super().__init__(y_size, x_size)
self.delay = delay
def simulate_visual(self, cycles=100, skip=5):
@ -151,15 +152,11 @@ class Visual_Heatmap_Simulator(Heatmap_Simulator):
print(f"Figure updated: {c}.")
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.pause(self.delay)
simulator = Visual_Heatmap_Simulator(28, 28, -0.5, 1)
simulator.simulate_visual(10000, 50)
class Heatmap_Image:
def __init__(self, heatmap, min_val, max_val):
self.min_val = min_val
@ -183,3 +180,14 @@ class Heatmap_Image:
def save(self, 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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