如何在for循环中仅打印一次语句

时间:2019-05-21 15:25:39

标签: python tensorflow

这是我的实时对象检测代码的一部分。(完整脚本:https://github.com/aswinr22/waste-model/blob/master/picamera1.py

import pandas as pd

#Existing DF where the data is in the form of list
df = pd.DataFrame(columns=['ID', 'value_list'])
#New DF where the data should be atomic
df_new = pd.DataFrame(columns=['ID', 'value_single'])

#Sample Data
row_1 = ['A', 'B', 'C', 'D']
row_2 = ['D', 'E', 'F']
row_3 = ['F', 'G']
row_4 = ['H', 'I']
row_5 = ['J']

#Data Push to existing DF
row_ = "row_"
for i in range(5):
    df.loc[i, 'ID'] = i
    df.loc[i, 'value_list'] = eval(row_+str(i+1))

#Data Push to new DF where list is pushed as atomic data
counter = 0
i=0
while(i<len(df)):
    j=0
    while(j<len(df['value_list'][i])):
        df_new.loc[counter, 'ID'] = df['ID'][i]
        df_new.loc[counter, 'value_single'] = df['value_list'][i][j]
        counter = counter + 1
        j = j+1
    i = i+1

print(df_new)

我的输出是这样:

for i in range (classes.size): # here is my classes id is retrieved
        if(classes[0][i] == 2 and scores[0][i]>0.5):
          print("e waste detected")

我要打印的语句仅一次。我该怎么办请帮助我

3 个答案:

答案 0 :(得分:0)

如果触发了条件,则可以使用break statement退出for循环。

编辑:在没有数据文件的情况下,很难与github上的代码完全兼容,但这是一个类似于您的用例的玩具示例:

classes= [0,2,2,1,2]

for item in (classes): # here is my classes id is retrieved
    if(item == 2):
        print("e waste detected")
        break
print("post-loop")

删除中断,您将看到现在看到的行为-但请注意缩进,它应位于if语句的内部。

答案 1 :(得分:0)

尝试一下(添加的代码带有#条新注释)

...
waste_found = False  # NEW
for frame1 in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):

    t1 = cv2.getTickCount()

    # Acquire frame and expand frame dimensions to have shape: [1, None, None, 3]
    # i.e. a single-column array, where each item in the column has the pixel RGB value
    frame = np.copy(frame1.array)
    frame.setflags(write=1)
    frame_expanded = np.expand_dims(frame, axis=0)

    # Perform the actual detection by running the model with the image as input
    (boxes, scores, classes, num) = sess.run(
        [detection_boxes, detection_scores, detection_classes, num_detections],
        feed_dict={image_tensor: frame_expanded})

    # Draw the results of the detection (aka 'visulaize the results')
    vis_util.visualize_boxes_and_labels_on_image_array(
        frame,
        np.squeeze(boxes),
        np.squeeze(classes).astype(np.int32),
        np.squeeze(scores),
        category_index,
        use_normalized_coordinates=True,
        line_thickness=8,
        min_score_thresh=0.40)
    # p = GPIO.PWM(servoPIN, 50)
    # p.start(2.5)
    for i in range(classes.size):
        if (classes[0][i] == 2 and scores[0][i] > 0.5):
            print("e waste detected")
            waste_found = True  # NEW
            break  # NEW
        # elif(classes[0][i] == 1 and scores[0][i]>0.5):
        # print("recycle detected")  
        # p.start(2.5) # Initialization
        ##  p.ChangeDutyCycle(5)
        # time.sleep(4)
        # p.ChangeDutyCycle(10)
        # time.sleep(4)
        #  except KeyboardInterrupt:
        #  p.stop()
        #  GPIO.cleanup()
    if waste_found:  # NEW
        break  # NEW

# return image_np

答案 2 :(得分:0)

wasted = (c==2 and s>0.5 for c, s  in zip(classes, scores))
if any(wasted):
  print("wasted detected")

双括号表示生成器理解,它在any发现第一个真值时停止。

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