Hi,

After successfully running python face detection example, I tried to modify the code in order to run vehicle and licence plate detection, but the model didn't detect anything. As I haven't figured out what's the issue, I would appreciate any suggestion regarding the problem.

The script I wrote looks as follows:

import cv2

def predict(frame, net):
    # Prepare input blob and perform an inference
    blob = cv2.dnn.blobFromImage(frame, size=(300, 300), ddepth=cv2.CV_8U)
    net.setInput(blob)
    out = net.forward()

    predictions = []

    # The net outputs a blob with the shape: [1, 1, N, 7], where N is the number of detected bounding boxes.
    # For each detection, the description has the format: [image_id, label, conf, x_min, y_min, x_max, y_max]

    # Draw detected faces on the frame
    for detection in out.reshape(-1, 7):
        image_id, label, conf, x_min, y_min, x_max, y_max = detection

        if conf > 0.5:
            predictions.append(detection)

    # return the list of predictions to the calling function
    return predictions

# Load the model
net = cv2.dnn.readNet('models/vehicle-license-plate-detection-barrier-0106.xml', 'models/vehicle-license-plate-detection-barrier-0106.bin')

# Specify target device
net.setPreferableTarget(cv2.dnn.DNN_TARGET_MYRIAD)

# Read an image
frame = cv2.imread('screenshots/mercedes.jpg')

predictions = predict(frame, net)

# Draw detected faces on the frame
for prediction in predictions:
    confidence = float(detection[2])
    xmin = int(detection[3] * frame.shape[1])
    ymin = int(detection[4] * frame.shape[0])
    xmax = int(detection[5] * frame.shape[1])
    ymax = int(detection[6] * frame.shape[0])

    cv2.rectangle(frame, (xmin, ymin), (xmax, ymax), color=(0, 255, 0))

# Save the frame to an image file
cv2.imwrite('out.png', frame)

Basically, I have downloaded the model files from this adddress and then modified input dimensions according to specifications.

To test the detection, I used the image attached below

The model I wanted to test is described here

Update

Now I tried to use vehicle-detection-adas-0002 model and it works. The differences I noticed are in the models:

• vehicle-license-plate-detection-barrier-0106 is a MobileNetV2 + SSD-based vehicle and license plate detector for the "Barrier" use case

• vehicle-detection-adas-0002 is a vehicle detection network based on an SSD framework with tuned MobileNet v1 as a feature extractor

So I guess these models might have to be initialized differently.