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draw detections when blobFromImages is used

Hello,

I was testing OpenCV face detection using a pre-trained model:

(h, w) = image.shape[:2]

net = cv2.dnn.readNetFromCaffe("deploy.prototxt.txt", "res10_300x300_ssd_iter_140000_fp16.caffemodel")
blob = cv2.dnn.blobFromImage(image, 1.0, (300, 300), [104., 117., 123.], False, False)
net.setInput(blob)
detections = net.forward()

for i in range(0, detections.shape[2]):
    confidence = detections[0, 0, i, 2]

    if confidence > 0.7:
        box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
        (startX, startY, endX, endY) = box.astype("int")

        text = "{:.2f}%".format(confidence * 100)
        y = startY - 10 if startY - 10 > 10 else startY + 10
        cv2.rectangle(image, (startX, startY), (endX, endY), (0, 0, 255), 2)
        cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)

This example is working ok. But I don't now how to modify the code above in order to draw the detections if two images are used instead of only one:

blob2 = cv2.dnn.blobFromImages(images, 1.0, (300, 300), [104., 117., 123.], False, True)
net.setInput(blob2)
detections = net.forward()

How to draw the detections?

Thanks in advanced

draw detections when blobFromImages is used

Hello,

I was testing OpenCV face detection using a pre-trained model:

(h, w) = image.shape[:2]

net = cv2.dnn.readNetFromCaffe("deploy.prototxt.txt", "res10_300x300_ssd_iter_140000_fp16.caffemodel")
blob = cv2.dnn.blobFromImage(image, 1.0, (300, 300), [104., 117., 123.], False, False)
net.setInput(blob)
detections = net.forward()

for i in range(0, detections.shape[2]):
    confidence = detections[0, 0, i, 2]

    if confidence > 0.7:
        box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
        (startX, startY, endX, endY) = box.astype("int")

        text = "{:.2f}%".format(confidence * 100)
        y = startY - 10 if startY - 10 > 10 else startY + 10
        cv2.rectangle(image, (startX, startY), (endX, endY), (0, 0, 255), 2)
        cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)

This example is working ok. But I don't now how to modify the code above in order to draw the detections if two images are used instead of only one:

blob2 = cv2.dnn.blobFromImages(images, 1.0, (300, 300), [104., 117., 123.], False, True)
False)
net.setInput(blob2)
detections = net.forward()

How to draw the detections?

Thanks in advanced

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retagged

updated 2019-01-11 23:40:05 -0500

berak gravatar image

draw detections when blobFromImages is used

Hello,

I was testing OpenCV face detection using a pre-trained model:

(h, w) = image.shape[:2]

net = cv2.dnn.readNetFromCaffe("deploy.prototxt.txt", "res10_300x300_ssd_iter_140000_fp16.caffemodel")
blob = cv2.dnn.blobFromImage(image, 1.0, (300, 300), [104., 117., 123.], False, False)
net.setInput(blob)
detections = net.forward()

for i in range(0, detections.shape[2]):
    confidence = detections[0, 0, i, 2]

    if confidence > 0.7:
        box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
        (startX, startY, endX, endY) = box.astype("int")

        text = "{:.2f}%".format(confidence * 100)
        y = startY - 10 if startY - 10 > 10 else startY + 10
        cv2.rectangle(image, (startX, startY), (endX, endY), (0, 0, 255), 2)
        cv2.putText(image, text, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)

This example is working ok. But I don't now how to modify the code above in order to draw the detections if two images are used instead of only one:

blob2 = cv2.dnn.blobFromImages(images, 1.0, (300, 300), [104., 117., 123.], False, False)
net.setInput(blob2)
detections = net.forward()

How to draw the detections?

Thanks in advanced