Vehicle-Counting / utils.py
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Add initial project structure with Streamlit UI and utility functions
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"""
Utility Functions
Kumpulan fungsi helper untuk drawing, resize, dan kalkulasi FPS.
Dipakai oleh app.py untuk rendering hasil deteksi dan tracking ke frame video.
"""
import cv2
import numpy as np
import time
# palette warna yang cukup kontras satu sama lain (BGR format)
COLOR_PALETTE = [
(255, 150, 50), # biru muda
(50, 255, 50), # hijau
(50, 100, 255), # oranye/merah
(255, 50, 200), # ungu/pink
(0, 255, 255), # kuning
(255, 255, 0), # cyan
(128, 0, 255), # magenta
(0, 165, 255), # oranye
]
# warna default kalau kelas tidak dikenali
DEFAULT_COLOR = (200, 200, 200)
# cache warna per class name supaya konsisten
_color_cache = {}
def get_class_color(class_name):
"""Ambil warna untuk class tertentu, konsisten selama runtime."""
if class_name not in _color_cache:
idx = len(_color_cache) % len(COLOR_PALETTE)
_color_cache[class_name] = COLOR_PALETTE[idx]
return _color_cache[class_name]
def draw_detections(frame, detections):
"""
Gambar bounding box dan label pada frame.
Args:
frame: numpy array (BGR image)
detections: list of dict dari detector.detect()
setiap dict punya: bbox, confidence, class_name
Returns:
frame yang sudah di-annotate
"""
annotated = frame.copy()
for det in detections:
bbox = det["bbox"]
x1, y1, x2, y2 = [int(v) for v in bbox]
conf = det["confidence"]
cls_name = det["class_name"]
color = get_class_color(cls_name)
# gambar rectangle
cv2.rectangle(annotated, (x1, y1), (x2, y2), color, 2)
# buat label
label = f"{cls_name} {conf:.2f}"
label_size, _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
# background label
cv2.rectangle(
annotated,
(x1, y1 - label_size[1] - 6),
(x1 + label_size[0] + 4, y1),
color,
-1
)
# text label
cv2.putText(
annotated, label,
(x1 + 2, y1 - 4),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, (255, 255, 255), 1
)
return annotated
def draw_tracking(frame, tracked_objects):
"""
Gambar bounding box dengan track ID pada frame.
Args:
frame: numpy array (BGR)
tracked_objects: list of dict dari tracker.update()
setiap dict punya: track_id, bbox, class_name, confidence
Returns:
frame yang sudah di-annotate
"""
annotated = frame.copy()
for obj in tracked_objects:
bbox = obj["bbox"]
x1, y1, x2, y2 = [int(v) for v in bbox]
track_id = obj["track_id"]
cls_name = obj["class_name"]
conf = obj["confidence"]
color = get_class_color(cls_name)
# gambar rectangle
cv2.rectangle(annotated, (x1, y1), (x2, y2), color, 2)
# label dengan ID
label = f"ID:{track_id} {cls_name} {conf:.2f}"
label_size, _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
cv2.rectangle(
annotated,
(x1, y1 - label_size[1] - 6),
(x1 + label_size[0] + 4, y1),
color,
-1
)
cv2.putText(
annotated, label,
(x1 + 2, y1 - 4),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, (255, 255, 255), 1
)
# gambar center point
cx, cy = obj["center"]
cv2.circle(annotated, (int(cx), int(cy)), 4, color, -1)
# gambar trajectory (beberapa titik terakhir)
history = obj.get("center_history", [])
if len(history) > 1:
for i in range(1, len(history)):
pt1 = (int(history[i-1][0]), int(history[i-1][1]))
pt2 = (int(history[i][0]), int(history[i][1]))
# fade effect: makin lama makin transparan
thickness = max(1, int(2 * (i / len(history))))
cv2.line(annotated, pt1, pt2, color, thickness)
return annotated
def draw_counting_line(frame, line_position_ratio, count_text=""):
"""
Gambar garis virtual horizontal pada frame.
Args:
frame: numpy array
line_position_ratio: rasio posisi garis (0.0 - 1.0)
count_text: text tambahan yang ditampilkan di dekat garis
Returns:
frame yang sudah digambar garisnya
"""
annotated = frame.copy()
h, w = frame.shape[:2]
line_y = int(h * line_position_ratio)
# garis utama (merah, tebal)
cv2.line(annotated, (0, line_y), (w, line_y), (0, 0, 255), 2)
# garis dashed effect (biar kelihatan lebih jelas)
dash_length = 20
for x in range(0, w, dash_length * 2):
x_end = min(x + dash_length, w)
cv2.line(annotated, (x, line_y), (x_end, line_y), (0, 255, 255), 3)
# label "COUNTING LINE"
cv2.putText(
annotated, "COUNTING LINE",
(10, line_y - 10),
cv2.FONT_HERSHEY_SIMPLEX,
0.6, (0, 255, 255), 2
)
if count_text:
cv2.putText(
annotated, count_text,
(10, line_y + 25),
cv2.FONT_HERSHEY_SIMPLEX,
0.6, (0, 255, 255), 2
)
return annotated
def draw_polygon_region(frame, polygon_points):
"""
Gambar polygon region pada frame.
Args:
frame: numpy array
polygon_points: list of (x, y) tuples
Returns:
frame dengan overlay polygon
"""
annotated = frame.copy()
if not polygon_points or len(polygon_points) < 3:
return annotated
pts = np.array(polygon_points, dtype=np.int32)
# gambar filled polygon semi-transparan
overlay = annotated.copy()
cv2.fillPoly(overlay, [pts], (0, 255, 0))
annotated = cv2.addWeighted(overlay, 0.2, annotated, 0.8, 0)
# gambar border polygon
cv2.polylines(annotated, [pts], isClosed=True, color=(0, 255, 0), thickness=2)
# label
cx = int(np.mean([p[0] for p in polygon_points]))
cy = int(np.mean([p[1] for p in polygon_points]))
cv2.putText(
annotated, "COUNTING REGION",
(cx - 80, cy),
cv2.FONT_HERSHEY_SIMPLEX,
0.6, (0, 255, 0), 2
)
return annotated
def draw_stats_overlay(frame, stats):
"""
Gambar overlay statistik di pojok kiri atas frame.
Args:
frame: numpy array
stats: dict berisi informasi yang mau ditampilkan
contoh: {"FPS": "24.5", "Total": "15", "Car": "8", ...}
Returns:
frame dengan overlay stats
"""
annotated = frame.copy()
h, w = frame.shape[:2]
# background semi-transparan
overlay = annotated.copy()
box_h = 30 + len(stats) * 25
cv2.rectangle(overlay, (5, 5), (200, box_h), (0, 0, 0), -1)
annotated = cv2.addWeighted(overlay, 0.6, annotated, 0.4, 0)
# render setiap stat
y_offset = 25
for key, value in stats.items():
text = f"{key}: {value}"
cv2.putText(
annotated, text,
(15, y_offset),
cv2.FONT_HERSHEY_SIMPLEX,
0.5, (255, 255, 255), 1
)
y_offset += 25
return annotated
def resize_frame(frame, max_width=1280):
"""
Resize frame supaya tidak terlalu besar untuk display.
Menjaga aspect ratio.
Args:
frame: numpy array
max_width: lebar maksimum
Returns:
frame yang sudah di-resize (atau frame asli kalau sudah cukup kecil)
"""
h, w = frame.shape[:2]
if w <= max_width:
return frame
scale = max_width / w
new_w = int(w * scale)
new_h = int(h * scale)
resized = cv2.resize(frame, (new_w, new_h), interpolation=cv2.INTER_AREA)
return resized
def calculate_fps(start_time, frame_count):
"""
Hitung FPS berdasarkan waktu mulai dan jumlah frame.
Args:
start_time: waktu mulai (dari time.time())
frame_count: jumlah frame yang sudah diproses
Returns:
float: FPS value
"""
elapsed = time.time() - start_time
if elapsed <= 0 or frame_count <= 0:
return 0.0
return frame_count / elapsed
def format_time(seconds):
"""
Format detik ke string mm:ss.
Args:
seconds: float, durasi dalam detik
Returns:
str: formatted time string
"""
minutes = int(seconds) // 60
secs = int(seconds) % 60
return f"{minutes:02d}:{secs:02d}"