Commit

README.md

@@ -1,12 +1,37 @@
 ---
 title: DemoIAZIKA
-emoji: 🦀
-colorFrom: pink
-colorTo: green
+emoji: 🦋
+colorFrom: blue
+colorTo: pink
 sdk: gradio
-sdk_version: 3.4.1
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Configuration
+
+`title`: _string_  
+Display title for the Space
+
+`emoji`: _string_  
+Space emoji (emoji-only character allowed)
+
+`colorFrom`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`colorTo`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`sdk`: _string_  
+Can be either `gradio` or `streamlit`
+
+`sdk_version` : _string_  
+Only applicable for `streamlit` SDK.  
+See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
+
+`app_file`: _string_  
+Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
+Path is relative to the root of the repository.
+
+`pinned`: _boolean_  
+Whether the Space stays on top of your list.

app.py

@@ -0,0 +1,115 @@
+# -*- 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 os
+import gradio as gr
+import torch
+from PIL import Image
+
+HF_TOKEN = os.getenv("HF_TOKEN")
+hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "demoIAZIKA-flags")
+
+# 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,
+                        allow_flagging="manual",
+                        flagging_options=["correcto", "incorrecto", "casi correcto", "error", "otro"],
+                        flagging_callback=hf_writer).launch(
+    enable_queue=True,
+    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)
+"""

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3306079ebeedfbc36f56650a8c9c4a73d97a394113e26a1117371bc0233cd439
+size 14348789

requirements.txt

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+# pip install -r requirements.txt
+# base ----------------------------------------
+matplotlib>=3.2.2
+numpy>=1.18.5
+opencv-python-headless
+Pillow
+PyYAML>=5.3.1
+scipy>=1.4.1
+torch>=1.7.0
+torchvision>=0.8.1
+tqdm>=4.41.0
+# logging -------------------------------------
+tensorboard>=2.4.1
+# wandb
+# plotting ------------------------------------
+seaborn>=0.11.0
+pandas
+# export --------------------------------------
+# coremltools>=4.1
+# onnx>=1.9.0
+# scikit-learn==0.19.2  # for coreml quantization
+# extras --------------------------------------
+# Cython  # for pycocotools https://github.com/cocodataset/cocoapi/issues/172
+# pycocotools>=2.0  # COCO mAP
+# albumentations>=1.0.3
+thop  # FLOPs computation