Klette_Computer_Vision_2019/part9/CodPython.py - main - Dev_Devil/ComputerVision

Klette_Computer_Vision_2019/part9/CodPython.py
184 строки6 KB
Geek_bro
part9
02 дек 2025, 20:55
02 дек 2025, 20:5551e9140
# -*- coding: utf-8 -*-
"""Untitled0.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/10Wxwz-mo4T1jUGGqfY6eS9r9GgweXcRS
"""

from google.colab import drive
drive.mount('/content/drive')

import os
os.listdir('/content')

# ============================================================
# ============== ЕДИНЫЙ КОД (ГЛАВА 9 — ПРИЗНАКИ) =============
# ============== ОБНАРУЖЕНИЕ, СОВПАДЕНИЕ, ТРЕКИНГ ===========
# ============================================================

!pip install opencv-contrib-python >/dev/null
import cv2
import numpy as np
import matplotlib.pyplot as plt

# --------------------------
# CONFIG — УКАЗЫВАЕШЬ СВОИ ФАЙЛЫ
# --------------------------
IMG1_PATH = "/content/image1.png"
IMG2_PATH = "/content/image2.png"
VIDEO_PATH = "/content/video.mp4"   # если нет видео → оставь пустым ""

# каждые сколько кадров показывать результат LK
LK_SHOW_EVERY = 10


# --------------------------
# Вспомогательные функции
# --------------------------
def show_img(img, title="Image", size=(8,6)):
    plt.figure(figsize=size)
    if img.ndim == 2:
        plt.imshow(img, cmap='gray')
    else:
        plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    plt.title(title)
    plt.axis('off')
    plt.show()

def load_gray(path):
    img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
    if img is None:
        raise FileNotFoundError(path)
    return img


# --------------------------
# ORB: детекция и описание
# --------------------------
def detect_orb(img, n_features=1000):
    orb = cv2.ORB_create(nfeatures=n_features)
    kp, desc = orb.detectAndCompute(img, None)
    return kp, desc

def draw_keypoints(img, kp, title):
    out = cv2.drawKeypoints(img, kp, None, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
    show_img(out, title)


# --------------------------
# Сопоставление дескрипторов
# --------------------------
def match_descriptors(desc1, desc2, ratio=0.75):
    bf = cv2.BFMatcher(cv2.NORM_HAMMING)
    pairs = bf.knnMatch(desc1, desc2, k=2)
    good = [m for m, n in pairs if m.distance < ratio * n.distance]
    return good

def draw_matches(img1, kp1, img2, kp2, matches, max_draw=50):
    matches = sorted(matches, key=lambda m: m.distance)[:max_draw]
    out = cv2.drawMatches(img1, kp1, img2, kp2, matches, None,
                          flags=cv2.DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS)
    show_img(out, "ORB Matches")


# --------------------------
# Lucas–Kanade трекинг (Colab-friendly)
# --------------------------
def lucas_kanade_colab(video_path, show_every=10):
    cap = cv2.VideoCapture(video_path)
    ret, old = cap.read()
    if not ret:
        print("Не удалось открыть видео")
        return

    old_gray = cv2.cvtColor(old, cv2.COLOR_BGR2GRAY)
    p0 = cv2.goodFeaturesToTrack(old_gray, maxCorners=300, qualityLevel=0.01, minDistance=7)

    # LK параметры
    lk_params = dict(
        winSize=(15, 15),
        maxLevel=3,
        criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 30, 0.01)
    )

    mask = np.zeros_like(old)

    frame_id = 0
    results = []

    while True:
        ret, frame = cap.read()
        if not ret:
            break

        frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None, **lk_params)
        if p1 is None:
            break

        good_new = p1[st == 1]
        good_old = p0[st == 1]

        for (x_new, y_new), (x_old, y_old) in zip(good_new, good_old):
            x_new, y_new = int(x_new), int(y_new)
            x_old, y_old = int(x_old), int(y_old)
            mask = cv2.line(mask, (x_new, y_new), (x_old, y_old), (0,255,0), 2)
            frame = cv2.circle(frame, (x_new, y_new), 3, (0,0,255), -1)

        combined = cv2.add(frame, mask)

        # Для COLAB — выводим изображение каждые N кадров
        if frame_id % show_every == 0:
            results.append(cv2.cvtColor(combined, cv2.COLOR_BGR2RGB))

        old_gray = frame_gray.copy()
        p0 = good_new.reshape(-1, 1, 2)
        frame_id += 1

    cap.release()

    # Показываем результаты
    print("Показ кадров LK (каждый N-й):")
    for i, img in enumerate(results):
        plt.figure(figsize=(8,6))
        plt.imshow(img)
        plt.title(f"LK frame {i}")
        plt.axis('off')
        plt.show()


# ============================================================
# ======================= MAIN PART ===========================
# ============================================================

# 1. Загружаем изображения
img1 = load_gray(IMG1_PATH)
img2 = load_gray(IMG2_PATH)

show_img(img1, "Image 1")
show_img(img2, "Image 2")

# 2. ORB признаки
kp1, desc1 = detect_orb(img1)
kp2, desc2 = detect_orb(img2)

print(f"Image1 ORB keypoints: {len(kp1)}")
print(f"Image2 ORB keypoints: {len(kp2)}")

draw_keypoints(img1, kp1, "ORB Keypoints (Image 1)")
draw_keypoints(img2, kp2, "ORB Keypoints (Image 2)")

# 3. Сопоставление
matches = match_descriptors(desc1, desc2)
print(f"Good matches: {len(matches)}")

draw_matches(img1, kp1, img2, kp2, matches)

# 4. Трекинг LK (опционально)
if VIDEO_PATH.strip():
    lucas_kanade_colab(VIDEO_PATH, show_every=LK_SHOW_EVERY)
else:
    print("Видео для LK не указано — трекинг пропущен.")