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| import numpy as np | |
| import pandas as pd | |
| import matplotlib.pylab as plt | |
| import PIL.Image as Image | |
| import tensorflow as tf | |
| import tensorflow_hub as hub | |
| import gradio as gr | |
| from einops import rearrange | |
| import s2cell | |
| from geopy.geocoders import Nominatim | |
| TF_MODEL_URL = 'https://tfhub.dev/google/planet/vision/classifier/planet_v2/1' | |
| IMAGE_SHAPE = (299, 299) | |
| labels=pd.read_csv('planet_v2_labelmap.csv') | |
| classifier = tf.keras.Sequential([hub.KerasLayer(TF_MODEL_URL, | |
| input_shape=IMAGE_SHAPE+(3,) | |
| )]) | |
| def classify_image(image): | |
| img = image/255.0 | |
| img = rearrange(img, 'h w c -> 1 h w c') | |
| prediction = classifier.predict(img) | |
| s2code = np.argmax(prediction) | |
| loc=labels['S2CellId'][s2code] | |
| location=s2cell.token_to_lat_lon(loc) | |
| geolocator = Nominatim(user_agent="coordinateconverter") | |
| address = location | |
| location_add = geolocator.reverse(address) | |
| return location,location_add | |
| title = 'Photo Geolocation' | |
| description = 'Just upload or drop an image to know where your photo is taken . ' | |
| article ='''PlaNet -Photo Geolocation with Convolutional Neural Networks. A gradio demo app for estimation of the address and coordinates of your photo. | |
| <div style='text-align: center;'>PlaNet : <a href='https://tfhub.dev/google/planet/vision/classifier/planet_v2/1' target='_blank'>Github Repo</a> | <a href='https://arxiv.org/pdf/1602.05314v1.pdf' target='_blank'>Paper</a></div>''' | |
| ex1 = 'UnitedKingdom_00019_964966881_426cf82f57_1071_98545448@N00.jpg' | |
| ex2 = 'Tanzania_00019_1292210091_693ea74b7a_1088_15274769@N00.jpg' | |
| ex3 = 'Sydney_00073_1226915900_eea86783cd_1128_65768710@N00.jpg' | |
| ex4 = 'HongKong_00041_504492617_7af38e0004_208_7224156@N03.jpg' | |
| iface = gr.Interface(classify_image, inputs=gr.inputs.Image(shape=(299, 299), image_mode="RGB", type="numpy"), | |
| outputs=[gr.outputs.Textbox(label='Latitude,Longitude'),gr.outputs.Textbox(label='Address')],examples=[ex1,ex2,ex3,ex4], | |
| live=False,layout="horizontal", interpretation=None,title=title, | |
| description=description, article=article) | |
| iface.launch() |