upload app

app.py

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+import gradio as gr
+import cv2
+import requests
+import gdown
+import tensorflow as tf
+from tensorflow import keras
+import numpy as np
+from PIL import Image
+from keras.models import load_model
+
+url = 'https://drive.google.com/file/d/1ueGC-MBuVip9jkfLJdfeH-RBy6fjDZ5j/view?usp=sharing'
+output_path = 'classes.txt'
+gdown.download(url, output_path, quiet=False,fuzzy=True)
+
+with open(output_path,'r') as file:
+    LABELS = [x.strip() for x in file.readlines()]
+
+
+num_classes = 200
+IMG_SIZE = 128
+
+model = load_model('model.h5')
+
+# Preprocess image
+def preprocess(image):
+  image = image.convert('RGB') # To RGB
+  image = image.resize((IMG_SIZE, IMG_SIZE)) # Resize the image to 128 x 128
+  image = np.array(image)
+  image = tf.keras.applications.mobilenet_v2.preprocess_input(image) # Rescale the pixel to [-1,1] for MobileNetV2
+  return image
+
+
+def predict(image):
+     image = preprocess(image)
+     image = np.expand_dims(image, axis=0) # Add batch dimension
+     prediction = model.predict(image) # Predict the image using the trained model
+
+     # Get the top 3 predictions
+     idx = np.argsort(prediction[0])[::-1][:3]
+     top3_value = np.asarray([prediction[0][i] for i in idx[0:3]])
+     top3_idx = idx[0:3]
+
+     return {LABELS[i]:str(v) for i,v in zip(top3_idx,top3_value)}
+
+# Create Gradio interface
+input_image = gr.inputs.Image(type='pil')
+output_text = 'label'
+app = gr.Interface(fn=predict, inputs=input_image, outputs=output_text)
+app.launch()

classes.txt

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+001.Black_footed_Albatross
+002.Laysan_Albatross
+003.Sooty_Albatross
+004.Groove_billed_Ani
+005.Crested_Auklet
+006.Least_Auklet
+007.Parakeet_Auklet
+008.Rhinoceros_Auklet
+009.Brewer_Blackbird
+010.Red_winged_Blackbird
+011.Rusty_Blackbird
+012.Yellow_headed_Blackbird
+013.Bobolink
+014.Indigo_Bunting
+015.Lazuli_Bunting
+016.Painted_Bunting
+017.Cardinal
+018.Spotted_Catbird
+019.Gray_Catbird
+020.Yellow_breasted_Chat
+021.Eastern_Towhee
+022.Chuck_will_Widow
+023.Brandt_Cormorant
+024.Red_faced_Cormorant
+025.Pelagic_Cormorant
+026.Bronzed_Cowbird
+027.Shiny_Cowbird
+028.Brown_Creeper
+029.American_Crow
+030.Fish_Crow
+031.Black_billed_Cuckoo
+032.Mangrove_Cuckoo
+033.Yellow_billed_Cuckoo
+034.Gray_crowned_Rosy_Finch
+035.Purple_Finch
+036.Northern_Flicker
+037.Acadian_Flycatcher
+038.Great_Crested_Flycatcher
+039.Least_Flycatcher
+040.Olive_sided_Flycatcher
+041.Scissor_tailed_Flycatcher
+042.Vermilion_Flycatcher
+043.Yellow_bellied_Flycatcher
+044.Frigatebird
+045.Northern_Fulmar
+046.Gadwall
+047.American_Goldfinch
+048.European_Goldfinch
+049.Boat_tailed_Grackle
+050.Eared_Grebe
+051.Horned_Grebe
+052.Pied_billed_Grebe
+053.Western_Grebe
+054.Blue_Grosbeak
+055.Evening_Grosbeak
+056.Pine_Grosbeak
+057.Rose_breasted_Grosbeak
+058.Pigeon_Guillemot
+059.California_Gull
+060.Glaucous_winged_Gull
+061.Heermann_Gull
+062.Herring_Gull
+063.Ivory_Gull
+064.Ring_billed_Gull
+065.Slaty_backed_Gull
+066.Western_Gull
+067.Anna_Hummingbird
+068.Ruby_throated_Hummingbird
+069.Rufous_Hummingbird
+070.Green_Violetear
+071.Long_tailed_Jaeger
+072.Pomarine_Jaeger
+073.Blue_Jay
+074.Florida_Jay
+075.Green_Jay
+076.Dark_eyed_Junco
+077.Tropical_Kingbird
+078.Gray_Kingbird
+079.Belted_Kingfisher
+080.Green_Kingfisher
+081.Pied_Kingfisher
+082.Ringed_Kingfisher
+083.White_breasted_Kingfisher
+084.Red_legged_Kittiwake
+085.Horned_Lark
+086.Pacific_Loon
+087.Mallard
+088.Western_Meadowlark
+089.Hooded_Merganser
+090.Red_breasted_Merganser
+091.Mockingbird
+092.Nighthawk
+093.Clark_Nutcracker
+094.White_breasted_Nuthatch
+095.Baltimore_Oriole
+096.Hooded_Oriole
+097.Orchard_Oriole
+098.Scott_Oriole
+099.Ovenbird
+100.Brown_Pelican
+101.White_Pelican
+102.Western_Wood_Pewee
+103.Sayornis
+104.American_Pipit
+105.Whip_poor_Will
+106.Horned_Puffin
+107.Common_Raven
+108.White_necked_Raven
+109.American_Redstart
+110.Geococcyx
+111.Loggerhead_Shrike
+112.Great_Grey_Shrike
+113.Baird_Sparrow
+114.Black_throated_Sparrow
+115.Brewer_Sparrow
+116.Chipping_Sparrow
+117.Clay_colored_Sparrow
+118.House_Sparrow
+119.Field_Sparrow
+120.Fox_Sparrow
+121.Grasshopper_Sparrow
+122.Harris_Sparrow
+123.Henslow_Sparrow
+124.Le_Conte_Sparrow
+125.Lincoln_Sparrow
+126.Nelson_Sharp_tailed_Sparrow
+127.Savannah_Sparrow
+128.Seaside_Sparrow
+129.Song_Sparrow
+130.Tree_Sparrow
+131.Vesper_Sparrow
+132.White_crowned_Sparrow
+133.White_throated_Sparrow
+134.Cape_Glossy_Starling
+135.Bank_Swallow
+136.Barn_Swallow
+137.Cliff_Swallow
+138.Tree_Swallow
+139.Scarlet_Tanager
+140.Summer_Tanager
+141.Artic_Tern
+142.Black_Tern
+143.Caspian_Tern
+144.Common_Tern
+145.Elegant_Tern
+146.Forsters_Tern
+147.Least_Tern
+148.Green_tailed_Towhee
+149.Brown_Thrasher
+150.Sage_Thrasher
+151.Black_capped_Vireo
+152.Blue_headed_Vireo
+153.Philadelphia_Vireo
+154.Red_eyed_Vireo
+155.Warbling_Vireo
+156.White_eyed_Vireo
+157.Yellow_throated_Vireo
+158.Bay_breasted_Warbler
+159.Black_and_white_Warbler
+160.Black_throated_Blue_Warbler
+161.Blue_winged_Warbler
+162.Canada_Warbler
+163.Cape_May_Warbler
+164.Cerulean_Warbler
+165.Chestnut_sided_Warbler
+166.Golden_winged_Warbler
+167.Hooded_Warbler
+168.Kentucky_Warbler
+169.Magnolia_Warbler
+170.Mourning_Warbler
+171.Myrtle_Warbler
+172.Nashville_Warbler
+173.Orange_crowned_Warbler
+174.Palm_Warbler
+175.Pine_Warbler
+176.Prairie_Warbler
+177.Prothonotary_Warbler
+178.Swainson_Warbler
+179.Tennessee_Warbler
+180.Wilson_Warbler
+181.Worm_eating_Warbler
+182.Yellow_Warbler
+183.Northern_Waterthrush
+184.Louisiana_Waterthrush
+185.Bohemian_Waxwing
+186.Cedar_Waxwing
+187.American_Three_toed_Woodpecker
+188.Pileated_Woodpecker
+189.Red_bellied_Woodpecker
+190.Red_cockaded_Woodpecker
+191.Red_headed_Woodpecker
+192.Downy_Woodpecker
+193.Bewick_Wren
+194.Cactus_Wren
+195.Carolina_Wren
+196.House_Wren
+197.Marsh_Wren
+198.Rock_Wren
+199.Winter_Wren
+200.Common_Yellowthroat

requirements.txt

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+# Base ----------------------------------------
+matplotlib>=3.2.2
+numpy>=1.21.6
+opencv-python>=4.6.0
+Pillow>=7.1.2
+PyYAML>=5.3.1
+requests>=2.23.0
+scipy>=1.4.1
+gradio>=3.36.1
+tensorflow==2.12.0
+tensorflow-datasets==4.9.2
+
+
+# Plotting ------------------------------------
+pandas>=1.1.4
+seaborn>=0.11.0
+gdown
+
+
+# Extras --------------------------------------
+psutil  # system utilization
+thop>=0.1.1  # FLOPs computation