Find and highlight characters in images
Find objects in images using text descriptions
Identify segments in an image using a Detectron2 model
State-of-the-art Zero-shot Object Detection
Identify objects in images
Generic YOLO Models Trained on COCO
Identify objects in real-time video feed
Detect objects in images
Detect objects in uploaded images
Detect objects in uploaded images
Detect objects in random images
Detect objects in images using drag-and-drop
Detect and measure areas of objects in images
Yolov5 Char is an object detection model specifically designed to find and highlight characters in images. It leverages the popular YOLOv5 architecture, known for its balance between speed and accuracy, to detect characters in various visual contexts. This tool is ideal for applications requiring character detection, such as text recognition, gaming, or media analysis.
Example:
from yolov5_char import detect
image_path = "path/to/image.jpg"
results = detect(image_path)
results.show()
What image formats does Yolov5 Char support?
Yolov5 Char supports common formats like JPEG, PNG, BMP, and TIFF.
How can I improve detection accuracy for small characters?
Adjust the model's confidence threshold and iou threshold to better detect small characters.
Are there any specific libraries required to run Yolov5 Char?
Yes, ensure you have PyTorch and OpenCV installed to run the model smoothly.