Hi,
Please check and share which is close to your usecase. We would need to reproduce the issue first and do checking. See if we can have further optimization.
Resizing the image can be done through NvBufSurface APIs in C. We are still working on the python bindings for this.
There are several topics about pythons bindings going on:
Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) rtx 2080 ti
• DeepStream Version 5 dp
• JetPack Version (valid for Jetson only)
• TensorRT Version 7
• NVIDIA GPU Driver Version (valid for GPU only) Driver Version: 440.64.00 CUDA Version: 10.2
I’m collecing the image with
n_frame = pyds.get_nvds_buf_surface(hash(gst_buffer), frame_meta.batch_id)
frame_image = np.array(n_frame, copy=True, order=‘C’)
frame_image = cv2.cvtColor(frame_i…
I’d like to know how these new bindings could be used. From the description of pyds.NvBufSurfaceMap() I got the impression that it is possible in python app to edit frame data located in NVMM memory. Am I correct? Right now I’m moving frames to host and do my custom drawing through standard gstreamer buffer map. But it would be nice to avoid host-device copies.
I saw the deepstream-imagedata-multistream example but it seems that changes made to frame in array returned from pyds.get_nvds_buf_su…