Does Primary detector of deepstream-app (detectnet_v2) outputs coverage map & bboxes?

• Hardware (V100)
• Network Type (Detectnet_v2)
• Training spec file
import cv2
import numpy as np
labels = [“Car”,“Bicycle”,“Person”,“Roadsign”]

MODEL_FILE = ‘resnet10.prototxt’
PRETRAINED = ‘resnet10.caffemodel’

load DNN model
nn = cv2.dnn.readNetFromCaffe(MODEL_FILE,PRETRAINED)
print(“[Status] loading model”)

read image from disk
image_name = ‘208_212_1631260113.jpg’
image = cv2.imread(image_name)
image_height, image_width, _ = image.shape
print(f"[Status] loading image")
print(f"Image resolution: {image.shape}")

create blob from image
print(f"[Status] creating blob from image")
blob = cv2.dnn.blobFromImage(
image, ### image
1, ### scalefactor
size = (640,368), ### size required by model
mean=(104, 117, 123), ### mean subtraction
swapRB = True)

Run inference
output = nn.forward())

I am loading the caffe model with OpenCV (code above) to run inference on an image. I am resizing the image to 640,368 as mentioned in prototxt file. Once run the inference, the output is an array of dimensions 1X4X23X40. Is this the coverage map? Where can I find the bboxes? Thank u!

Hello @gaia17, Have you configured the deepstream-app config and run this program? Please share the config and error that you met, thanks.

There is no update from you for a period, assuming this is not an issue any more.
Hence we are closing this topic. If need further support, please open a new one.

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