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Running
on
Zero
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Basic object detection example using Rex Omni
"""
import torch
from PIL import Image
from rex_omni import RexOmniVisualize, RexOmniWrapper
def main():
# Model path - replace with your actual model path
model_path = "IDEA-Research/Rex-Omni"
# Create wrapper with custom parameters
rex_model = RexOmniWrapper(
model_path=model_path,
backend="transformers", # or "vllm" for faster inference
max_tokens=4096,
temperature=0.0,
top_p=0.05,
top_k=1,
repetition_penalty=1.05,
)
# Load imag
image_path = "tutorials/detection_example/test_images/cafe.jpg" # Replace with your image path
image = Image.open(image_path).convert("RGB")
# Object detection
categories = [
"man",
"woman",
"yellow flower",
"sofa",
"robot-shope light",
"blanket",
"microwave",
"laptop",
"cup",
"white chair",
"lamp",
]
results = rex_model.inference(images=image, task="detection", categories=categories)
# Print results
result = results[0]
if result["success"]:
predictions = result["extracted_predictions"]
vis_image = RexOmniVisualize(
image=image,
predictions=predictions,
font_size=20,
draw_width=5,
show_labels=True,
)
# Save visualization
output_path = "tutorials/detection_example/test_images/cafe_visualize.jpg"
vis_image.save(output_path)
print(f"Visualization saved to: {output_path}")
else:
print(f"Inference failed: {result['error']}")
if __name__ == "__main__":
main()
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