添加一个光流跟踪

data/1.OpenCV初阶/6.视频分析/1.光流/flow.md

+# 蚂蚁的轨迹
+
+使用OpenCV光流分析，跟踪蚂蚁的轨迹
+
+![](./ant_flow.jpg)
+
+代码框架：
+
+```python
+import numpy as np
+import cv2
+
+if __name__ == '__main__':
+    cap = cv2.VideoCapture('ant.mp4')
+
+    # ShiTomasi 角点检测参数
+    feature_params = dict(
+        maxCorners=100,
+        qualityLevel=0.5,
+        minDistance=30,
+        blockSize=10
+    )
+
+    # Lucas Kanada 光流检测参数
+    lk_params = dict(
+        winSize=(15, 15),
+        maxLevel=2,
+        criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03)
+    )
+
+    # 获取第一帧并发现角点
+    ret, last_current_frame = cap.read()
+    last_gray = cv2.cvtColor(last_current_frame, cv2.COLOR_BGR2GRAY)
+
+    p0 = cv2.goodFeaturesToTrack(last_gray, mask=None, **feature_params)
+    mask = np.zeros_like(last_current_frame)
+
+    color = np.random.randint(0, 255, (100, 3))
+    while (1):
+        ret, current_frame = cap.read()
+
+        if not ret:
+            break
+
+        current_gray = cv2.cvtColor(current_frame, cv2.COLOR_BGR2GRAY)
+
+        # TODO(You): 请在此编写光流跟踪和绘制代码
+
+        current_img = cv2.add(current_frame, mask)
+        cv2.imshow('current_img', current_img)
+
+        k = cv2.waitKey(30) & 0xff
+        if k == 27:
+            break
+
+        last_gray = current_gray.copy()
+        p0 = good_new.reshape(-1, 1, 2)
+
+    cv2.destroyAllWindows()
+    cap.release()
+
+```
+
+## 答案
+
+```python
+p1, st, err = cv2.calcOpticalFlowPyrLK(
+    last_gray, current_gray, p0, None, **lk_params)
+
+good_new = p1[st == 1]
+good_old = p0[st == 1]
+
+for i, (new, old) in enumerate(zip(good_new, good_old)):
+    a, b = new.ravel()
+    c, d = old.ravel()
+    a, b = int(a), int(b)
+    c, d = int(c), int(d)
+    mask = cv2.line(mask, (a, b), (c, d), color[i].tolist(), 2)
+    current_frame = cv2.circle(
+        current_frame, (a, b), 5, color[i].tolist(), -1)
+```
+
+## 选项
+
+### current_gray, last_gray顺序错误
+
+```python
+p1, st, err = cv2.calcOpticalFlowPyrLK(
+    current_gray, last_gray, p0, None, **lk_params)
+
+good_new = p1[st == 1]
+good_old = p0[st == 1]
+
+for i, (new, old) in enumerate(zip(good_new, good_old)):
+    a, b = new.ravel()
+    c, d = old.ravel()
+    a, b = int(a), int(b)
+    c, d = int(c), int(d)
+    mask = cv2.line(mask, (a, b), (c, d), color[i].tolist(), 2)
+    current_frame = cv2.circle(
+        current_frame, (a, b), 5, color[i].tolist(), -1)
+```
+
+### a,b,c,d 没有转换整型
+
+```python
+p1, st, err = cv2.calcOpticalFlowPyrLK(
+    last_gray, current_gray, p0, None, **lk_params)
+
+good_new = p1[st == 1]
+good_old = p0[st == 1]
+
+for i, (new, old) in enumerate(zip(good_new, good_old)):
+    a, b = new.ravel()
+    c, d = old.ravel()
+    mask = cv2.line(mask, (a, b), (c, d), color[i].tolist(), 2)
+    current_frame = cv2.circle(
+        current_frame, (a, b), 5, color[i].tolist(), -1)
+```
+
+### good_new 和 good_new 顺序错误
+
+```python
+p1, st, err = cv2.calcOpticalFlowPyrLK(
+    last_gray, current_gray, p0, None, **lk_params)
+
+good_old = p1[st == 1]
+good_new = p0[st == 1]
+
+for i, (new, old) in enumerate(zip(good_new, good_old)):
+    a, b = new.ravel()
+    c, d = old.ravel()
+    a, b = int(a), int(b)
+    c, d = int(c), int(d)
+    mask = cv2.line(mask, (a, b), (c, d), color[i].tolist(), 2)
+    current_frame = cv2.circle(
+        current_frame, (a, b), 5, color[i].tolist(), -1)
+```

data/1.OpenCV初阶/6.视频分析/1.光流/flow.py

+import numpy as np
+import cv2
+
+if __name__ == '__main__':
+    cap = cv2.VideoCapture('ant.mp4')
+
+    # ShiTomasi 角点检测参数
+    feature_params = dict(
+        maxCorners=100,
+        qualityLevel=0.5,
+        minDistance=30,
+        blockSize=10
+    )
+
+    # Lucas Kanada 光流检测参数
+    lk_params = dict(
+        winSize=(15, 15),
+        maxLevel=2,
+        criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03)
+    )
+
+    # 获取第一帧并发现角点
+    ret, last_current_frame = cap.read()
+    last_gray = cv2.cvtColor(last_current_frame, cv2.COLOR_BGR2GRAY)
+
+    p0 = cv2.goodFeaturesToTrack(last_gray, mask=None, **feature_params)
+    mask = np.zeros_like(last_current_frame)
+
+    color = np.random.randint(0, 255, (100, 3))
+    while (1):
+        ret, current_frame = cap.read()
+
+        if not ret:
+            break
+
+        current_gray = cv2.cvtColor(current_frame, cv2.COLOR_BGR2GRAY)
+
+        p1, st, err = cv2.calcOpticalFlowPyrLK(
+            last_gray, current_gray, p0, None, **lk_params)
+
+        good_new = p1[st == 1]
+        good_old = p0[st == 1]
+
+        for i, (new, old) in enumerate(zip(good_new, good_old)):
+            a, b = new.ravel()
+            c, d = old.ravel()
+            a, b = int(a), int(b)
+            c, d = int(c), int(d)
+            mask = cv2.line(mask, (a, b), (c, d), color[i].tolist(), 2)
+            current_frame = cv2.circle(
+                current_frame, (a, b), 5, color[i].tolist(), -1)
+
+        current_img = cv2.add(current_frame, mask)
+        cv2.imshow('current_img', current_img)
+
+        k = cv2.waitKey(30) & 0xff
+        if k == 27:
+            break
+
+        last_gray = current_gray.copy()
+        p0 = good_new.reshape(-1, 1, 2)
+
+    cv2.destroyAllWindows()
+    cap.release()

requirement.txt

 pre_commit~=2.16.0
-GitPython~=3.1.24
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+GitPython~=3.1.24
+filterpy==1.4.5
\ No newline at end of file