python image streaming from a buffer optimization

I am working on Python + flask in an embedded device with limited computing power.

I would like to stream a video, using images (RGBa) stored on the device as a pixels array. Currently, I am able to receive the video but the overall performance is not sufficient to get a smooth output.

Here is the current optimization I already did :

• reduce the number of copies by reading into the memory region
• remove the color alpha since it is not used.
• reduce by 4 the size of the image

    from PIL import Image

    @bp.route("/stream")
    def stream():
        def loop():
            yield b"--frame\r\n"
            while True:
               raw_data = view[ frame_id * BUF_SIZE : (frame_id + 1) * BUF_SIZE ]
               image_np = np.frombuffer(np.asarray(raw_stream[::]),
                          dtype=np.uint8
                          ).reshape((600, 1024, 4))
               img_byte_arr = io.BytesIO()
               jpeg_img = Image.fromarray(image_np[::4, ::4, :3], mode="RGB")
               jpeg_img.save(img_byte_arr, format="JPEG")
               yield (
                  b"Content-Type: image/jpeg\r\n\r\n"
                  + img_byte_arr.getvalue()
                  + b"\r\n--frame\r\n"
               )
        return Response(loop(), mimetype="multipart/x-mixed-replace; boundary=frame")

Based on some mesurement it seems that the operation Image.fromarray(image_np[::4, ::4, :3], mode="RGB") is the bottleneck since it tooks up to 0.2sec to be executed (10FPS).

Is there another way of converting an array to an image (JPEG or whatever format) that could speed up the process? Maybe another library than PIL?