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
