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学习OpenMV

發布時間:2024/1/1 编程问答 31 豆豆
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在這里插入代碼片 #學習OpenMV 2020.7.23
輸出print
列表List
if如果相等則是==
冪運算**
累加要先給存儲的變量賦初值 初始為0
for 變量 in range(100)
sum=sum+變量
最后要print(sum)才能得到最后的值

for循環 and while循環
for+變量+in range(范圍,終值值,步長值):

函數定義
def 函數名(參數):
功能語句
return 返回值
下面展示一些 內聯代碼片。

```python# Single Color RGB565 Blob Tracking Example # # This example shows off single color RGB565 tracking using the OpenMV Cam.import sensor, image, time, maththreshold_index = 0 # 0 for red, 1 for green, 2 for blue# Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max) # The below thresholds track in general red/green/blue things. You may wish to tune them... thresholds = [(30, 100, 15, 127, 15, 127), # generic_red_thresholds(30, 100, -64, -8, -32, 32), # generic_green_thresholds(0, 30, 0, 64, -128, 0)] # generic_blue_thresholdssensor.reset() #初始化相機傳感器 sensor.set_pixformat(sensor.RGB565)#設置相機的傳感器模式 sensor.set_framesize(sensor.QVGA)#設置相機模塊幀的大小 sensor.skip_frames(time = 2000)#跳過2000毫秒的幀 sensor.set_auto_gain(False) # must be turned off for color tracking #關閉自動增益 sensor.set_auto_whitebal(False) # must be turned off for color tracking clock = time.clock()# 關閉自動白平衡# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are # returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the # camera resolution. "merge=True" merges all overlapping blobs in the image.while(True):clock.tick()img = sensor.snapshot()for blob in img.find_blobs([thresholds[threshold_index]], pixels_threshold=200, area_threshold=200, merge=True):# These values depend on the blob not being circular - otherwise they will be shaky.if blob.elongation() > 0.5:img.draw_edges(blob.min_corners(), color=(255,0,0))img.draw_line(blob.major_axis_line(), color=(0,255,0))img.draw_line(blob.minor_axis_line(), color=(0,0,255))# These values are stable all the time.img.draw_rectangle(blob.rect())#在圖像上繪制一個矩形img.draw_cross(blob.cx(), blob.cy())#在圖像上繪制一個十字# Note - the blob rotation is unique to 0-180 only.img.draw_keypoints([(blob.cx(), blob.cy(), int(math.degrees(blob.rotation())))], size=20)print(clock.fps())#在圖像上繪制關鍵點

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