Change image quality, resolution, FPS

General
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1

Hi everyone! I’m using pi 5 + ai hailo 8L hat.

Is there any way I can change the image resolution, the quality of image and the FPS?
When I use YOLO with the hailo_rpi5_examples the image quality is awesome, but when I use DeGirum, the quality is not that good, is there any way I can change that?
I’m using DeGirum so I can analyize multiple cameras at the same time, with different models on each camera.

I’m new in this AI edge world and the job you did guys is great! Super easy to work with.

Thank you!

2

Hi @ody777, welcome to the world of edge AI! We’re glad to hear you’re finding our tools are easy to work with.

To thoroughly help you, could you please share the code you used with DeGirum PySDK? That will help us pinpoint what the issue is.

In the meantime, here are some quick tips:

1. Control Image Resolution and Quality

In DeGirum PySDK, the quality of the input video frame depends primarily on how the video frames are captured or preprocessed. If you’re using OpenCV or PiCamera2 to read frames, you can increase the resolution by setting it explicitly:

Example for OpenCV:

stream = cv2.VideoCapture(0)
stream.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
stream.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)

You can also perform transformations (e.g., resize, rotate) using a custom frame generator before passing frames to predict_batch:

def high_res_frame_generator(video_source):
    stream = cv2.VideoCapture(video_source)
    stream.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
    stream.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
    while True:
        ret, frame = stream.read()
        if not ret:
            break
        yield frame
    stream.release()

Pass this to:

for result in model.predict_batch(high_res_frame_generator(0)):
    cv2.imshow("Overlay", result.image_overlay)

2. Enhance Overlay Appearance

You can improve the visual appearance of the overlay using model options:

model = dg.load_model(
    model_name="your_model",
    inference_host_address="@local",
    zoo_url="degirum/hailo",
    device_type="HAILORT/HAILO8L",
    overlay_show_labels=True,
    overlay_show_probabilities=True,
    overlay_font_scale=1.5,
    overlay_line_width=3,
    overlay_color=[(0, 255, 0)],
    overlay_alpha=1.0
)

3. Increase FPS

To maximize FPS:

  • Use predict_batch() to process frames as a stream, reducing latency.
  • Minimize display or post-processing overhead in your Python code.
  • Benchmark raw device speed using hailortcli (raw FPS) and pysdkProfile.py (actual app FPS).
  • Ensure the input source (e.g., webcam or RTSP) can actually deliver high FPS—camera limitations often cap effective throughput.