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app.py

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+### 1. Imports and class names setup ###
+import gradio as gr
+import os 
+import torch
+
+from model import create_effnetb2_model
+from timeit import default_timer as timer
+from typing import Tuple, Dict
+
+# Setup class names
+class_names = ['AFRICAN CROWNED CRANE',
+ 'AFRICAN FIREFINCH',
+ 'ALBATROSS',
+ 'ALEXANDRINE PARAKEET',
+ 'AMERICAN AVOCET',
+ 'AMERICAN BITTERN',
+ 'AMERICAN COOT',
+ 'AMERICAN GOLDFINCH',
+ 'AMERICAN KESTREL',
+ 'AMERICAN PIPIT',
+ 'AMERICAN REDSTART',
+ 'ANHINGA',
+ 'ANNAS HUMMINGBIRD',
+ 'ANTBIRD',
+ 'ARARIPE MANAKIN',
+ 'ASIAN CRESTED IBIS',
+ 'BALD EAGLE',
+ 'BALD IBIS',
+ 'BALI STARLING',
+ 'BALTIMORE ORIOLE',
+ 'BANANAQUIT',
+ 'BANDED BROADBILL',
+ 'BANDED PITA',
+ 'BAR-TAILED GODWIT',
+ 'BARN OWL',
+ 'BARN SWALLOW',
+ 'BARRED PUFFBIRD',
+ 'BAY-BREASTED WARBLER',
+ 'BEARDED BARBET',
+ 'BEARDED BELLBIRD',
+ 'BEARDED REEDLING',
+ 'BELTED KINGFISHER',
+ 'BIRD OF PARADISE',
+ 'BLACK & YELLOW bROADBILL',
+ 'BLACK BAZA',
+ 'BLACK FRANCOLIN',
+ 'BLACK SKIMMER',
+ 'BLACK SWAN',
+ 'BLACK TAIL CRAKE',
+ 'BLACK THROATED BUSHTIT',
+ 'BLACK THROATED WARBLER',
+ 'BLACK VULTURE',
+ 'BLACK-CAPPED CHICKADEE',
+ 'BLACK-NECKED GREBE',
+ 'BLACK-THROATED SPARROW',
+ 'BLACKBURNIAM WARBLER',
+ 'BLONDE CRESTED WOODPECKER',
+ 'BLUE COAU',
+ 'BLUE GROUSE',
+ 'BLUE HERON',
+ 'BLUE THROATED TOUCANET',
+ 'BOBOLINK',
+ 'BORNEAN BRISTLEHEAD',
+ 'BORNEAN LEAFBIRD',
+ 'BORNEAN PHEASANT',
+ 'BRANDT CORMARANT',
+ 'BROWN CREPPER',
+ 'BROWN NOODY',
+ 'BROWN THRASHER',
+ 'BULWERS PHEASANT',
+ 'CACTUS WREN',
+ 'CALIFORNIA CONDOR',
+ 'CALIFORNIA GULL',
+ 'CALIFORNIA QUAIL',
+ 'CANARY',
+ 'CAPE GLOSSY STARLING',
+ 'CAPE MAY WARBLER',
+ 'CAPPED HERON',
+ 'CAPUCHINBIRD',
+ 'CARMINE BEE-EATER',
+ 'CASPIAN TERN',
+ 'CASSOWARY',
+ 'CEDAR WAXWING',
+ 'CERULEAN WARBLER',
+ 'CHARA DE COLLAR',
+ 'CHESTNET BELLIED EUPHONIA',
+ 'CHIPPING SPARROW',
+ 'CHUKAR PARTRIDGE',
+ 'CINNAMON TEAL',
+ 'CLARKS NUTCRACKER',
+ 'COCK OF THE  ROCK',
+ 'COCKATOO',
+ 'COLLARED ARACARI',
+ 'COMMON FIRECREST',
+ 'COMMON GRACKLE',
+ 'COMMON HOUSE MARTIN',
+ 'COMMON LOON',
+ 'COMMON POORWILL',
+ 'COMMON STARLING',
+ 'COUCHS KINGBIRD',
+ 'CRESTED AUKLET',
+ 'CRESTED CARACARA',
+ 'CRESTED NUTHATCH',
+ 'CRIMSON SUNBIRD',
+ 'CROW',
+ 'CROWNED PIGEON',
+ 'CUBAN TODY',
+ 'CUBAN TROGON',
+ 'CURL CRESTED ARACURI',
+ 'D-ARNAUDS BARBET',
+ 'DARK EYED JUNCO',
+ 'DOUBLE BARRED FINCH',
+ 'DOUBLE BRESTED CORMARANT',
+ 'DOWNY WOODPECKER',
+ 'EASTERN BLUEBIRD',
+ 'EASTERN MEADOWLARK',
+ 'EASTERN ROSELLA',
+ 'EASTERN TOWEE',
+ 'ELEGANT TROGON',
+ 'ELLIOTS  PHEASANT',
+ 'EMPEROR PENGUIN',
+ 'EMU',
+ 'ENGGANO MYNA',
+ 'EURASIAN GOLDEN ORIOLE',
+ 'EURASIAN MAGPIE',
+ 'EVENING GROSBEAK',
+ 'FAIRY BLUEBIRD',
+ 'FIRE TAILLED MYZORNIS',
+ 'FLAME TANAGER',
+ 'FLAMINGO',
+ 'FRIGATE',
+ 'GAMBELS QUAIL',
+ 'GANG GANG COCKATOO',
+ 'GILA WOODPECKER',
+ 'GILDED FLICKER',
+ 'GLOSSY IBIS',
+ 'GO AWAY BIRD',
+ 'GOLD WING WARBLER',
+ 'GOLDEN CHEEKED WARBLER',
+ 'GOLDEN CHLOROPHONIA',
+ 'GOLDEN EAGLE',
+ 'GOLDEN PHEASANT',
+ 'GOLDEN PIPIT',
+ 'GOULDIAN FINCH',
+ 'GRAY CATBIRD',
+ 'GRAY KINGBIRD',
+ 'GRAY PARTRIDGE',
+ 'GREAT GRAY OWL',
+ 'GREAT KISKADEE',
+ 'GREAT POTOO',
+ 'GREATOR SAGE GROUSE',
+ 'GREEN BROADBILL',
+ 'GREEN JAY',
+ 'GREEN MAGPIE',
+ 'GREY PLOVER',
+ 'GROVED BILLED ANI',
+ 'GUINEA TURACO',
+ 'GUINEAFOWL',
+ 'GYRFALCON',
+ 'HARLEQUIN DUCK',
+ 'HARPY EAGLE',
+ 'HAWAIIAN GOOSE',
+ 'HELMET VANGA',
+ 'HIMALAYAN MONAL',
+ 'HOATZIN',
+ 'HOODED MERGANSER',
+ 'HOOPOES',
+ 'HORNBILL',
+ 'HORNED GUAN',
+ 'HORNED LARK',
+ 'HORNED SUNGEM',
+ 'HOUSE FINCH',
+ 'HOUSE SPARROW',
+ 'HYACINTH MACAW',
+ 'IMPERIAL SHAQ',
+ 'INCA TERN',
+ 'INDIAN BUSTARD',
+ 'INDIAN PITTA',
+ 'INDIAN ROLLER',
+ 'INDIGO BUNTING',
+ 'IWI',
+ 'JABIRU',
+ 'JAVA SPARROW',
+ 'KAGU',
+ 'KAKAPO',
+ 'KILLDEAR',
+ 'KING VULTURE',
+ 'KIWI',
+ 'KOOKABURRA',
+ 'LARK BUNTING',
+ 'LAZULI BUNTING',
+ 'LILAC ROLLER',
+ 'LONG-EARED OWL',
+ 'MAGPIE GOOSE',
+ 'MALABAR HORNBILL',
+ 'MALACHITE KINGFISHER',
+ 'MALAGASY WHITE EYE',
+ 'MALEO',
+ 'MALLARD DUCK',
+ 'MANDRIN DUCK',
+ 'MANGROVE CUCKOO',
+ 'MARABOU STORK',
+ 'MASKED BOOBY',
+ 'MASKED LAPWING',
+ 'MIKADO  PHEASANT',
+ 'MOURNING DOVE',
+ 'MYNA',
+ 'NICOBAR PIGEON',
+ 'NOISY FRIARBIRD',
+ 'NORTHERN CARDINAL',
+ 'NORTHERN FLICKER',
+ 'NORTHERN FULMAR',
+ 'NORTHERN GANNET',
+ 'NORTHERN GOSHAWK',
+ 'NORTHERN JACANA',
+ 'NORTHERN MOCKINGBIRD',
+ 'NORTHERN PARULA',
+ 'NORTHERN RED BISHOP',
+ 'NORTHERN SHOVELER',
+ 'OCELLATED TURKEY',
+ 'OKINAWA RAIL',
+ 'ORANGE BRESTED BUNTING',
+ 'ORIENTAL BAY OWL',
+ 'OSPREY',
+ 'OSTRICH',
+ 'OVENBIRD',
+ 'OYSTER CATCHER',
+ 'PAINTED BUNTIG',
+ 'PALILA',
+ 'PARADISE TANAGER',
+ 'PARAKETT  AKULET',
+ 'PARUS MAJOR',
+ 'PATAGONIAN SIERRA FINCH',
+ 'PEACOCK',
+ 'PELICAN',
+ 'PEREGRINE FALCON',
+ 'PHILIPPINE EAGLE',
+ 'PINK ROBIN',
+ 'POMARINE JAEGER',
+ 'PUFFIN',
+ 'PURPLE FINCH',
+ 'PURPLE GALLINULE',
+ 'PURPLE MARTIN',
+ 'PURPLE SWAMPHEN',
+ 'PYGMY KINGFISHER',
+ 'QUETZAL',
+ 'RAINBOW LORIKEET',
+ 'RAZORBILL',
+ 'RED BEARDED BEE EATER',
+ 'RED BELLIED PITTA',
+ 'RED BROWED FINCH',
+ 'RED FACED CORMORANT',
+ 'RED FACED WARBLER',
+ 'RED FODY',
+ 'RED HEADED DUCK',
+ 'RED HEADED WOODPECKER',
+ 'RED HONEY CREEPER',
+ 'RED NAPED TROGON',
+ 'RED TAILED HAWK',
+ 'RED TAILED THRUSH',
+ 'RED WINGED BLACKBIRD',
+ 'RED WISKERED BULBUL',
+ 'REGENT BOWERBIRD',
+ 'RING-NECKED PHEASANT',
+ 'ROADRUNNER',
+ 'ROBIN',
+ 'ROCK DOVE',
+ 'ROSY FACED LOVEBIRD',
+ 'ROUGH LEG BUZZARD',
+ 'ROYAL FLYCATCHER',
+ 'RUBY THROATED HUMMINGBIRD',
+ 'RUDY KINGFISHER',
+ 'RUFOUS KINGFISHER',
+ 'RUFUOS MOTMOT',
+ 'SAMATRAN THRUSH',
+ 'SAND MARTIN',
+ 'SANDHILL CRANE',
+ 'SATYR TRAGOPAN',
+ 'SCARLET CROWNED FRUIT DOVE',
+ 'SCARLET IBIS',
+ 'SCARLET MACAW',
+ 'SCARLET TANAGER',
+ 'SHOEBILL',
+ 'SHORT BILLED DOWITCHER',
+ 'SMITHS LONGSPUR',
+ 'SNOWY EGRET',
+ 'SNOWY OWL',
+ 'SORA',
+ 'SPANGLED COTINGA',
+ 'SPLENDID WREN',
+ 'SPOON BILED SANDPIPER',
+ 'SPOONBILL',
+ 'SPOTTED CATBIRD',
+ 'SRI LANKA BLUE MAGPIE',
+ 'STEAMER DUCK',
+ 'STORK BILLED KINGFISHER',
+ 'STRAWBERRY FINCH',
+ 'STRIPED OWL',
+ 'STRIPPED MANAKIN',
+ 'STRIPPED SWALLOW',
+ 'SUPERB STARLING',
+ 'SWINHOES PHEASANT',
+ 'TAIWAN MAGPIE',
+ 'TAKAHE',
+ 'TASMANIAN HEN',
+ 'TEAL DUCK',
+ 'TIT MOUSE',
+ 'TOUCHAN',
+ 'TOWNSENDS WARBLER',
+ 'TREE SWALLOW',
+ 'TROPICAL KINGBIRD',
+ 'TRUMPTER SWAN',
+ 'TURKEY VULTURE',
+ 'TURQUOISE MOTMOT',
+ 'UMBRELLA BIRD',
+ 'VARIED THRUSH',
+ 'VENEZUELIAN TROUPIAL',
+ 'VERMILION FLYCATHER',
+ 'VICTORIA CROWNED PIGEON',
+ 'VIOLET GREEN SWALLOW',
+ 'VULTURINE GUINEAFOWL',
+ 'WALL CREAPER',
+ 'WATTLED CURASSOW',
+ 'WHIMBREL',
+ 'WHITE BROWED CRAKE',
+ 'WHITE CHEEKED TURACO',
+ 'WHITE NECKED RAVEN',
+ 'WHITE TAILED TROPIC',
+ 'WHITE THROATED BEE EATER',
+ 'WILD TURKEY',
+ 'WILSONS BIRD OF PARADISE',
+ 'WOOD DUCK',
+ 'YELLOW BELLIED FLOWERPECKER',
+ 'YELLOW CACIQUE',
+ 'YELLOW HEADED BLACKBIRD']
+
+### 2. Model and transforms perparation ###
+vit, vit_transforms = create_transformer_model(
+    num_classes=325)
+
+# Load save weights
+vit.load_state_dict(
+    torch.load(
+        f="bird_classification_vit.pth",
+        map_location=torch.device("cpu") # load the model to the CPU
+    )
+)
+
+### 3. Predict function ### 
+
+def predict(img) -> Tuple[Dict, float]:
+  # Start a timer
+  start_time = timer()
+
+  # Transform the input image for use with EffNetB2
+  img = vit_transforms(img).unsqueeze(0) # unsqueeze = add batch dimension on 0th index
+
+  # Put model into eval mode, make prediction
+  vit.eval()
+  with torch.inference_mode():
+    # Pass transformed image through the model and turn the prediction logits into probaiblities
+    pred_probs = torch.softmax(effnetb2(img), dim=1)
+
+  # Create a prediction label and prediction probability dictionary
+  pred_labels_and_probs = {class_names[i]: float(pred_probs[0][i]) for i in range(len(class_names))}
+
+  # Calculate pred time
+  end_time = timer()
+  pred_time = round(end_time - start_time, 4)
+
+  # Return pred dict and pred time
+  return pred_labels_and_probs, pred_time
+
+### 4. Gradio app ### 
+
+# Create title, description and article
+title = "Bird Species Classification"
+description = "A [Transformer] computer vision model to classify Bird species.."
+article = "Created by Chidera Stanley [Transformer using PyTorch]"
+
+# Create example list
+example_list = [["examples/" + example] for example in os.listdir("examples")]
+
+# Create the Gradio demo
+app = gr.Interface(fn=predict, # maps inputs to outputs
+                    inputs=gr.Image(type="pil"),
+                    outputs=[gr.Label(num_top_classes=3, label="Predictions"),
+                             gr.Number(label="Prediction time (s)")],
+                    examples=example_list,
+                    title=title,
+                    description=description,
+                    article=article)
+
+# Launch the demo!
+app.launch() 

bird_classification_vit.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d052c78bae58442b8a357ffcad5ca504e1393934b66b88bae71672aff542287f
+size 344256753

model.py

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+import torch
+import torchvision
+
+from torch import nn
+
+def create_transformer_model(num_classes:int=325, # default output classes = 3 (pizza, steak, sushi)
+                          seed:int=42):
+  # 1, 2, 3 Create EffNetB2 pretrained weights, transforms and model
+  weights = torchvision.models.ViT_B_16_Weights.DEFAULT
+  transforms = weights.transforms()
+  model = torchvision.models.vit_b_16(weights=weights)
+
+  # 4. Freeze all layers in the base model
+  for param in model.parameters():
+    param.requires_grad = False
+
+  # 5. Change classifier head with random seed for reproducibility
+  torch.manual_seed(seed)
+  model.classifier = nn.Sequential(
+      nn.Dropout(p=0.3, inplace=True),
+      nn.Linear(in_features=768, out_features=num_classes)
+  )
+
+  return model, transforms

requirements.txt

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+torch==1.12.0
+torchvision==0.13.0
+gradio==3.1.4