Ollama

https://blog.youkuaiyun.com/dannisklx/article/details/140782542

https://modelscope.cn/models/goldsj/GroundingDINO/files

pip3 install autodistill autodistill-yolov8 autodistill-grounding-dino

import os
HOME = os.getcwd()
print(HOME)



IMAGE_DIR_PATH = f"{HOME}/public_data"


import supervision as sv

image_paths = sv.list_files_with_extensions(
    directory=IMAGE_DIR_PATH,
    extensions=["png", "jpg", "jpg"])

print('image count:', len(image_paths))


import cv2
SAMPLE_SIZE = 16
SAMPLE_GRID_SIZE = (4, 4)
SAMPLE_PLOT_SIZE = (16, 16)
titles = [
    image_path.stem
    for image_path
    in image_paths[:SAMPLE_SIZE]]
images = [
    cv2.imread(str(image_path))
    for image_path
    in image_paths[:SAMPLE_SIZE]]

sv.plot_images_grid(images=images, titles=titles, grid_size=SAMPLE_GRID_SIZE, size=SAMPLE_PLOT_SIZE)


from autodistill.detection import CaptionOntology

ontology=CaptionOntology({
    "goods": "goods"
})


DATASET_DIR_PATH = f"{HOME}/public_dataset"


from autodistill_grounding_dino import GroundingDINO
base_model = GroundingDINO(ontology=ontology)
dataset = base_model.label(
    input_folder=IMAGE_DIR_PATH,
    extension=".jpg",
    output_folder=DATASET_DIR_PATH)

ANNOTATIONS_DIRECTORY_PATH = f"{HOME}/public_dataset/train/labels"
IMAGES_DIRECTORY_PATH = f"{HOME}/public_dataset/train/images"
DATA_YAML_PATH = f"{HOME}/public_dataset/data.yaml"


print(ANNOTATIONS_DIRECTORY_PATH)
print(IMAGES_DIRECTORY_PATH)
print(DATA_YAML_PATH)


import supervision as sv

dataset = sv.DetectionDataset.from_yolo(
    images_directory_path=IMAGES_DIRECTORY_PATH,
    annotations_directory_path=ANNOTATIONS_DIRECTORY_PATH,
    data_yaml_path=DATA_YAML_PATH)

len(dataset)


import supervision as sv

image_names = list(dataset.images.keys())[:SAMPLE_SIZE]

mask_annotator = sv.MaskAnnotator()
box_annotator = sv.BoxAnnotator()

images = []
for image_name in image_names:
    image = dataset.images[image_name]
    annotations = dataset.annotations[image_name]
    labels = [
        dataset.classes[class_id]
        for class_id
        in annotations.class_id]
    annotates_image = mask_annotator.annotate(
        scene=image.copy(),
        detections=annotations)
    annotates_image = box_annotator.annotate(
        scene=annotates_image,
        detections=annotations,
        labels=labels)
    images.append(annotates_image)

sv.plot_images_grid(
    images=images,
    titles=image_names,
    grid_size=SAMPLE_GRID_SIZE,
    size=SAMPLE_PLOT_SIZE)

from autodistill_yolov8 import YOLOv8

target_model = YOLOv8("yolov8n.pt")
target_model.train(DATA_YAML_PATH, epochs=100)