| |
| """stat_lab_10.ipynb |
| |
| Automatically generated by Colaboratory. |
| |
| Original file is located at |
| https://colab.research.google.com/drive/1M9jt20Xv08CFH0RJOpWe8aXT62PqGrKu |
| """ |
|
|
| !python -m pip install transformers accelerate sentencepiece emoji pythainlp --quiet |
| !python -m pip install --no-deps thai2transformers==0.1.2 --quiet |
|
|
| """# image Detection""" |
|
|
| !pip install timm |
|
|
| """## pipline""" |
|
|
| |
| from transformers import pipeline |
|
|
| pipe = pipeline("object-detection", model="facebook/detr-resnet-50") |
|
|
| """## Load model""" |
|
|
| |
| from transformers import AutoFeatureExtractor, AutoModelForObjectDetection |
|
|
| extractor = AutoFeatureExtractor.from_pretrained("facebook/detr-resnet-50") |
| model = AutoModelForObjectDetection.from_pretrained("facebook/detr-resnet-50") |
|
|
| """## Use model""" |
|
|
| from transformers import DetrImageProcessor, DetrForObjectDetection |
| import torch |
| from PIL import Image |
| import requests |
|
|
| url = "http://images.cocodataset.org/val2017/000000039769.jpg" |
| image = Image.open(requests.get(url, stream=True).raw) |
|
|
| processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50") |
| model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50") |
|
|
| inputs = processor(images=image, return_tensors="pt") |
| outputs = model(**inputs) |
|
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| |
| |
| target_sizes = torch.tensor([image.size[::-1]]) |
| results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0] |
|
|
| for score, label, box in zip(results["scores"], results["labels"], results["boxes"]): |
| box = [round(i, 2) for i in box.tolist()] |
| print( |
| f"Detected {model.config.id2label[label.item()]} with confidence " |
| f"{round(score.item(), 3)} at location {box}" |
| ) |
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