add files

app.py

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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'
+
+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],
+            live=False,layout="horizontal", interpretation=None,title=title,
+              description=description, article=article)
+
+iface.launch()             

requirements.txt

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+
+einops
+s2cell
+numpy
+pandas
+matplotlib.pylab
+PIL
+geopy.geocoders 
+tensorflow
+tensorflow_hub