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# Import necessary libraries | |
import warnings | |
from ultralytics import YOLO # Ensure ultralytics is installed | |
from transformers import pipeline, DetrImageProcessor | |
# Suppress unnecessary warnings | |
warnings.filterwarnings("ignore", message=".*copying from a non-meta parameter.*") | |
# Setup the image processor | |
processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50", use_fast=True) | |
# Load the YOLO model (make sure ultralytics is installed) | |
model = YOLO("yolov5s.pt") # Change to the model you are using | |
# Your model inference or other operations | |
# Example detection function | |
def detect_objects(image): | |
# Use your model for object detection | |
results = model(image) | |
return results | |
# Call the function | |
image = "path_to_image.jpg" # Replace with your image path | |
detection_results = detect_objects(image) | |
print(detection_results) | |