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import math, random, time
from dataclasses import dataclass, field
from typing import List, Optional, Tuple
import gradio as gr
from PIL import Image, ImageDraw
W, H = 900, 540
ROOM = (60, 40, W - 60, H - 40)
DT = 0.05
MAX_SPEED_BASE = 65.0
PERSON_RADIUS = 6
EXIT_W, EXIT_H = 28, 68
C_BG = (245, 246, 248, 255)
C_ROOM = (250, 250, 250, 255)
C_BORDER = (28, 28, 28, 255)
C_OBS = (175, 178, 185, 255)
C_EXIT = (52, 132, 255, 255)
C_CALM = (44, 184, 78, 255)
C_ALERT = (250, 191, 35, 255)
C_PANIC = (233, 68, 68, 255)
C_INCIDENT = (230, 60, 60, 96)
RUNNING = False
@dataclass
class Person:
x: float; y: float; vx: float; vy: float
stress: float = 0.0; state: int = 0; evacuated: bool = False
def color(self): return [C_CALM, C_ALERT, C_PANIC][self.state]
@dataclass
class ExitZone:
x: int; y: int; w: int = EXIT_W; h: int = EXIT_H
def rect(self): return (self.x, self.y, self.x + self.w, self.y + self.h)
@dataclass
class World:
width: int = W; height: int = H; room: Tuple[int,int,int,int] = ROOM
people: List[Person] = field(default_factory=list)
exits: List[ExitZone] = field(default_factory=list)
incident: Optional[Tuple[int,int,int]] = None
speed_scale: float = 1.0; cohesion: float = 0.3; separation: float = 0.6
panic_spread: float = 2.0; personal_space: float = 22.0
def step(self, dt: float):
def nearest_exit_vec(px, py):
best=None; best_d2=1e12
for ex in self.exits:
cx, cy = ex.x + ex.w/2, ex.y + ex.h/2
dx, dy = cx - px, cy - py
d2 = dx*dx + dy*dy
if d2 < best_d2: best_d2, best = d2, (dx, dy)
return best or (0.0, 0.0)
for p in self.people:
if p.evacuated: continue
gx, gy = nearest_exit_vec(p.x, p.y)
p.vx += gx*0.002; p.vy += gy*0.002
v = math.hypot(p.vx, p.vy)
vmax = MAX_SPEED_BASE*self.speed_scale
if v > vmax: p.vx, p.vy = p.vx/v*vmax, p.vy/v*vmax
p.x += p.vx*dt; p.y += p.vy*dt
for ex in self.exits:
x0, y0, x1, y1 = ex.rect()
if x0 <= p.x <= x1 and y0 <= p.y <= y1:
p.evacuated = True
def render(self):
img = Image.new("RGBA", (self.width, self.height), C_BG)
d = ImageDraw.Draw(img, "RGBA")
d.rectangle(self.room, fill=C_ROOM, outline=C_BORDER, width=3)
for ex in self.exits:
d.rectangle(ex.rect(), fill=C_EXIT)
d.text((ex.x+6, ex.y+ex.h/2-7), "Exit", fill=(255,255,255,255))
for p in self.people:
if not p.evacuated:
d.ellipse((p.x-4, p.y-4, p.x+4, p.y+4), fill=p.color())
return img
def make_world(n_people=200):
w = World()
ex1 = ExitZone(x=ROOM[2]-8-EXIT_W, y=int(ROOM[1]+70))
ex2 = ExitZone(x=ROOM[2]-8-EXIT_W, y=int(ROOM[3]-70-EXIT_H))
w.exits = [ex1, ex2]
for _ in range(n_people):
w.people.append(Person(random.randint(100, 700), random.randint(100, 400), 0, 0))
return w
def reset_fn(n_people):
w = make_world(int(n_people))
return w.render(), w
def start_fn(world):
global RUNNING; RUNNING = True
while RUNNING:
world.step(DT)
yield world.render(), world
time.sleep(DT)
def pause_fn():
global RUNNING; RUNNING = False
return gr.update(), gr.update()
with gr.Blocks(title="Behavioral ML in Virtual Crowds") as demo:
gr.Markdown("## Behavioral ML in Virtual Crowds · eenvoudige simulatie")
img = gr.Image(label="Simulatie")
n_people = gr.Slider(10, 500, value=200, step=10, label="Aantal mensen")
start_btn = gr.Button("▶️ Start")
pause_btn = gr.Button("⏸️ Pauze")
reset_btn = gr.Button("🔁 Reset")
state = gr.State()
reset_btn.click(reset_fn, [n_people], [img, state])
start_btn.click(start_fn, [state], [img, state])
pause_btn.click(pause_fn, outputs=[img, state])
if __name__ == "__main__":
demo.launch()
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