Mauricio Guerta
commited on
Commit
•
4364716
1
Parent(s):
2c15167
Cria projeto Yolov5 modificado
Browse files
app1.py
ADDED
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import gradio as gr
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import torch
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import json
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import yolov5
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# Images
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torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg', 'zidane.jpg')
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torch.hub.download_url_to_file('https://raw.githubusercontent.com/WongKinYiu/yolov7/main/inference/images/image3.jpg', 'image3.jpg')
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torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/releases/download/v5.0/yolov5s.pt','yolov5s.pt')
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model_path = "yolov5s.pt" #"yolov5m.pt", "yolov5l.pt", "yolov5x.pt",
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image_size = 640,
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conf_threshold = 0.25,
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iou_threshold = 0.45,
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model = yolov5.load(model_path, device="cpu")
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def yolov5_inference(
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image: gr.inputs.Image = None,
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):
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"""
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YOLOv5 inference function
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Args:
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image: Input image
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model_path: Path to the model
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image_size: Image size
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conf_threshold: Confidence threshold
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iou_threshold: IOU threshold
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Returns:
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Rendered image
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"""
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results = model([image], size=image_size)
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tensor = {
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"tensorflow": [
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]
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}
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if results.pred is not None:
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for i, element in enumerate(results.pred[0]):
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object = {}
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#print (element[0])
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itemclass = round(element[5].item())
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object["classe"] = itemclass
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object["nome"] = results.names[itemclass]
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object["score"] = element[4].item()
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object["x"] = element[0].item()
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object["y"] = element[1].item()
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object["w"] = element[2].item()
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object["h"] = element[3].item()
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tensor["tensorflow"].append(object)
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text = json.dumps(tensor)
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#print (text)
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return text #results.render()[0]
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inputs = [
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gr.inputs.Image(type="pil", label="Input Image"),
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]
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outputs = gr.outputs.Image(type="filepath", label="Output Image")
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title = "YOLOv5"
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description = "YOLOv5 is a family of object detection models pretrained on COCO dataset. This model is a pip implementation of the original YOLOv5 model."
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examples = [['zidane.jpg'], ['image3.jpg']]
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demo_app = gr.Interface(
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fn=yolov5_inference,
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inputs=inputs,
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outputs=["text"],
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title=title,
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examples=examples,
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#cache_examples=True,
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#live=True,
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#theme='huggingface',
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)
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demo_app.launch(debug=True, server_name="192.168.0.153", server_port=8081, enable_queue=True)
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demo_app.launch(debug=True, enable_queue=True)
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#demo_app.launch(debug=True, server_port=8083, enable_queue=True)
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