Spaces:
Runtime error
Runtime error
| # -*- coding: utf-8 -*- | |
| """Deploy OceanApp demo.ipynb | |
| Automatically generated by Colaboratory. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1j0T8gdLIa0X8fzkIgFpXDoU27BF49RUz?usp=sharing | |
|  | |
| # Modelo | |
| YOLO es una familia de modelos de detecci贸n 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 | |
|  | |
| Este Notebook se acelera opcionalmente con un entorno de ejecuci贸n de GPU | |
| ---------------------------------------------------------------------- | |
| YOLOv5 Gradio demo | |
| *Author: Ultralytics LLC and Gradio* | |
| # C贸digo | |
| """ | |
| #!pip install -qr https://raw.githubusercontent.com/ultralytics/yolov5/master/requirements.txt gradio # install dependencies | |
| import gradio as gr | |
| import torch | |
| import logging | |
| from PIL import Image | |
| # Images | |
| torch.hub.download_url_to_file('https://i.pinimg.com/564x/18/0b/00/180b00e454362ff5caabe87d9a763a6f.jpg', 'ejemplo1.jpg') | |
| torch.hub.download_url_to_file('https://i.pinimg.com/564x/3b/2f/d4/3b2fd4b6881b64429f208c5f32e5e4be.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): | |
| try: | |
| '''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]) | |
| except Exception as e: | |
| logging.error(e, exc_info=True) | |
| #------------ Interface------------- | |
| in1 = gr.inputs.Radio(['640', '1280'], label="Tama帽o 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 = 'OceanApp' | |
| description = """ | |
| <p> | |
| <center> | |
| Sistema para el reconocimiento de las especies en la pesca acompa帽ante de cerco, utilizando redes neuronales convolucionales para una empresa del sector pesquero en los puertos de callao y paracas. | |
| <img src="https://i.pinimg.com/564x/3e/b8/f7/3eb8f7c348dffd7b3dffcafe81fbf2a6.jpg" 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 | |
| [](https://zenodo.org/badge/latestdoi/264818686) | |
| """ |