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app.py

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-# -*- coding: utf-8 -*-
-"""Deploy Barcelo demo.ipynb
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1FxaL8DcYgvjPrWfWruSA5hvk3J81zLY9
-
-![   ](https://www.vicentelopez.gov.ar/assets/images/logo-mvl.png)
-
-# Modelo
-
-YOLO es una familia de modelos de detección de objetos a escala compuesta entrenados en COCO dataset, e incluye una funcionalidad simple para Test Time Augmentation (TTA), model ensembling, hyperparameter evolution, and export to ONNX, CoreML and TFLite.
-
-
-## Gradio Inferencia
-
-![](https://i.ibb.co/982NS6m/header.png)
-
-Este Notebook se acelera opcionalmente con un entorno de ejecución de GPU
-
-
-----------------------------------------------------------------------
-
- YOLOv5 Gradio demo
-
-*Author: Ultralytics LLC and Gradio*
-
-# Código
-"""
-
-#!pip install -qr https://raw.githubusercontent.com/ultralytics/yolov5/master/requirements.txt gradio # install dependencies
-
-import gradio as gr
-import torch
-from PIL import Image
-
-# Images
-torch.hub.download_url_to_file('https://i.pinimg.com/originals/7f/5e/96/7f5e9657c08aae4bcd8bc8b0dcff720e.jpg', 'ejemplo1.jpg')
-torch.hub.download_url_to_file('https://i.pinimg.com/originals/c2/ce/e0/c2cee05624d5477ffcf2d34ca77b47d1.jpg', 'ejemplo2.jpg')
-
-# Model
-#model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # force_reload=True to update
-
-#model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt')  # local model  o google colab
-model = torch.hub.load('ultralytics/yolov5', 'custom', path='best.pt', force_reload=True, autoshape=True)  # local model  o google colab
-#model = torch.hub.load('path/to/yolov5', 'custom', path='/content/yolov56.pt', source='local')  # local repo
-
-
-def yolo(size, iou, conf, im):
-    '''Wrapper fn for gradio'''
-    g = (int(size) / max(im.size))  # gain
-    im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS)  # resize
-
-    model.iou = iou
-    
-    model.conf = conf
-
-   
-    results2 = model(im)  # inference
-   
-    results2.render()  # updates results.imgs with boxes and labels
-    return Image.fromarray(results2.ims[0])
-
-#------------ Interface-------------
-
-
-
-in1 = gr.inputs.Radio(['640', '1280'], label="Tamaño de la imagen", default='640', type='value')
-in2 = gr.inputs.Slider(minimum=0, maximum=1, step=0.05, default=0.45, label='NMS IoU threshold')
-in3 = gr.inputs.Slider(minimum=0, maximum=1, step=0.05, default=0.50, label='Umbral o  threshold')
-in4 = gr.inputs.Image(type='pil', label="Original Image")
-
-out2 = gr.outputs.Image(type="pil", label="YOLOv5")
-#-------------- Text-----
-title = 'Trampas Barceló'
-description = """
-<p>
-<center>
-Sistemas de Desarrollado por Subsecretaría de Innovación del Municipio de Vicente López. Advertencia solo usar fotos provenientes de las trampas Barceló, no de celular o foto de internet.
-<img src="https://www.vicentelopez.gov.ar/assets/images/logo-mvl.png" alt="logo" width="250"/>
-</center>
-</p>
-"""
-article ="<p style='text-align: center'><a href='https://docs.google.com/presentation/d/1T5CdcLSzgRe8cQpoi_sPB4U170551NGOrZNykcJD0xU/edit?usp=sharing' target='_blank'>Para mas info, clik para ir al white paper</a></p><p style='text-align: center'><a href='https://drive.google.com/drive/folders/1owACN3HGIMo4zm2GQ_jf-OhGNeBVRS7l?usp=sharing ' target='_blank'>Google Colab Demo</a></p><p style='text-align: center'><a href='https://github.com/Municipalidad-de-Vicente-Lopez/Trampa_Barcelo' target='_blank'>Repo Github</a></p></center></p>"
-          
-examples = [['640',0.45, 0.75,'ejemplo1.jpg'], ['640',0.45, 0.75,'ejemplo2.jpg']]
-
-iface = gr.Interface(yolo, inputs=[in1, in2, in3, in4], outputs=out2, title=title, description=description, article=article, examples=examples,theme="huggingface", analytics_enabled=False).launch(
-    debug=True)
-
-iface.launch()
-
-"""For YOLOv5 PyTorch Hub inference with **PIL**, **OpenCV**, **Numpy** or **PyTorch** inputs please see the full [YOLOv5 PyTorch Hub Tutorial](https://github.com/ultralytics/yolov5/issues/36).
-
-
-## Citation
-
-[![DOI](https://zenodo.org/badge/264818686.svg)](https://zenodo.org/badge/latestdoi/264818686)
-"""