diff --git a/.gitignore b/.gitignore index cdd2532..ae953e8 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,2 @@ -bird_cnn/data/ \ No newline at end of file +bird_cnn/data/ +bird_cnn/saved_models/ \ No newline at end of file diff --git a/bird_cnn/Dockerfile b/bird_cnn/Dockerfile new file mode 100644 index 0000000..98db0a1 --- /dev/null +++ b/bird_cnn/Dockerfile @@ -0,0 +1,16 @@ +FROM python:3.11-slim + +# Set working directory +WORKDIR /app + +# Copy requirements first (better Docker layer caching) +COPY . . + +# Install Python dependencies +RUN pip install --no-cache-dir -r requirements.txt + +# Make sure the startup script is executable +RUN chmod +x start_server.sh + +# Use the script as the container entrypoint +ENTRYPOINT ["./start_server.sh"] \ No newline at end of file diff --git a/bird_cnn/House_Crow.jpg b/bird_cnn/House_Crow.jpg new file mode 100644 index 0000000..7eec745 Binary files /dev/null and b/bird_cnn/House_Crow.jpg differ diff --git a/bird_cnn/__pycache__/bird_cnn.cpython-314.pyc b/bird_cnn/__pycache__/bird_cnn.cpython-314.pyc index 040f7ad..94d52af 100644 Binary files a/bird_cnn/__pycache__/bird_cnn.cpython-314.pyc and b/bird_cnn/__pycache__/bird_cnn.cpython-314.pyc differ diff --git a/bird_cnn/__pycache__/server.cpython-314.pyc b/bird_cnn/__pycache__/server.cpython-314.pyc index 65954ff..5d1ddf5 100644 Binary files a/bird_cnn/__pycache__/server.cpython-314.pyc and b/bird_cnn/__pycache__/server.cpython-314.pyc differ diff --git a/bird_cnn/bird_cnn.py b/bird_cnn/bird_cnn.py index a43a205..991a52c 100644 --- a/bird_cnn/bird_cnn.py +++ b/bird_cnn/bird_cnn.py @@ -3,26 +3,77 @@ import os import torch import torch.nn as nn import torch.nn.functional as F -import numpy as np from tqdm import tqdm +class SeparableConvolution(nn.Module): + def __init__(self, c_in, c_out, kernel_size): + super().__init__() + self.depthwise = nn.Conv2d(c_in, c_in, kernel_size, groups=c_in, padding=kernel_size//2) + self.bn1 = nn.BatchNorm2d(c_in) + self.pointwise = nn.Conv2d(c_in, c_out, kernel_size=1) + self.bn2 = nn.BatchNorm2d(c_out) + + def forward(self, x): + x = self.depthwise(x) + x = self.bn1(x) + x = F.relu(x) + + x = self.pointwise(x) + x = self.bn2(x) + x = F.relu(x) + + return x + class Bird_CNN(nn.Module): - def __init__(self, c_in, c_hidden, c_out, kernel_size, img_width, img_height): + def __init__(self, c_in, c_hidden, c_out): super().__init__() - self.model = nn.Sequential( - nn.Conv2d(c_in, c_hidden, kernel_size, padding=kernel_size//2), - nn.ReLU(), - nn.Conv2d(c_hidden, c_hidden, kernel_size, padding=kernel_size//2), + self.conv_init = nn.Sequential( + nn.Conv2d(c_in, c_hidden, kernel_size=3, padding=1), + nn.BatchNorm2d(c_hidden), nn.ReLU(), - - nn.Flatten(), - nn.Linear(c_hidden * img_height * img_width, c_out) + nn.Conv2d(c_hidden, c_hidden, 3, stride=2, padding=1) ) + # 1x1 conv branch + self.branch1 = SeparableConvolution(c_in=c_hidden, c_out=64, kernel_size=1) + + # 1x1 -> 3x3 conv branch + self.branch2 = SeparableConvolution(c_in=c_hidden, c_out=128, kernel_size=3) + + # 1x1 -> 5x5 conv branch + self.branch3 = SeparableConvolution(c_in=c_hidden, c_out=32, kernel_size=5) + + # 3x3 max pooling -> 1x1 conv branch + self.branch4 = nn.Sequential( + nn.MaxPool2d(kernel_size=3, stride=1, padding=1), + nn.Conv2d(c_hidden, 32, kernel_size=1), + nn.ReLU() + ) + + self.avgpool = nn.AdaptiveAvgPool2d((1, 1)) + self.flatten = nn.Flatten() + self.linear = nn.Linear(256, c_out) + + self.dropout = nn.Dropout(0.3) + def forward(self, x): - return self.model(x) + x = self.conv_init(x) + + b1 = self.branch1(x) + b2 = self.branch2(x) + b3 = self.branch3(x) + b4 = self.branch4(x) + + x = torch.cat([b1, b2, b3, b4], dim=1) + x = F.relu(x) + x = self.avgpool(x) + x = torch.flatten(x, 1) + + x = self.dropout(x) + + return self.linear(x) def trainCNN(model, optimizer, loss_module, train_data_loader, validation_data_loader, device, num_epochs, SAVE_PATH, save=False): @@ -79,7 +130,7 @@ def trainCNN(model, optimizer, loss_module, train_data_loader, validation_data_l save_dir = os.path.join(SAVE_PATH, "bird_cnn") os.makedirs(save_dir, exist_ok=True) - save_path = os.path.join(save_dir, "bird_cnn") + save_path = os.path.join(save_dir, f"bird_cnn{epoch+1}") torch.save(model.state_dict(), save_path) print(f"epoch: {epoch+1} | train accuracy: {int(train_acc * 1000) / 10}% | validation accuracy: {int(val_acc * 1000) / 10}%") diff --git a/bird_cnn/main.py b/bird_cnn/main.py index 7ea43d9..2937282 100644 --- a/bird_cnn/main.py +++ b/bird_cnn/main.py @@ -34,13 +34,13 @@ val_size = len(dataset) - train_size train_dataset, val_dataset = random_split(dataset, [train_size, val_size]) -train_loader = DataLoader(train_dataset, batch_size=32, shuffle=True) -val_loader = DataLoader(val_dataset, batch_size=32, shuffle=False) +train_loader = DataLoader(train_dataset, batch_size=26, shuffle=True) +val_loader = DataLoader(val_dataset, batch_size=26, shuffle=False) device = torch.device("cpu") if not torch.cuda.is_available() else torch.device("cuda:0") print("Using device", device) -model = Bird_CNN(c_in=3, c_hidden=15, c_out=7, kernel_size=3, img_width=IMAGE_SIZE[0], img_height=IMAGE_SIZE[1]) +model = Bird_CNN(c_in=3, c_hidden=15, c_out=7) model.to(device) optimizer = torch.optim.Adam(model.parameters(), lr=1e-3, weight_decay=1e-4) loss_module = nn.CrossEntropyLoss() diff --git a/bird_cnn/requirements.txt b/bird_cnn/requirements.txt new file mode 100644 index 0000000..5ba1753 --- /dev/null +++ b/bird_cnn/requirements.txt @@ -0,0 +1,7 @@ +fastapi==0.136.1 +networkx==3.6.1 +numpy==2.3.4 +torch==2.11.0+cu126 +torchvision==0.26.0+cu126 +tqdm==4.67.3 +uvicorn==0.46.0 diff --git a/bird_cnn/server.py b/bird_cnn/server.py index 646ab35..7a63d2a 100644 --- a/bird_cnn/server.py +++ b/bird_cnn/server.py @@ -4,6 +4,7 @@ import os import torch from torchvision import transforms from fastapi import FastAPI, File, UploadFile +from fastapi.middleware.cors import CORSMiddleware from PIL import Image import io import torch.nn.functional as F @@ -43,6 +44,18 @@ model.eval() app = FastAPI() +origins = [ + "http://localhost:5173", +] + +app.add_middleware( + CORSMiddleware, + allow_origins=origins, + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + @app.post("/predict") async def predict(file: UploadFile = File(...)): image_bytes = await file.read() diff --git a/bird_cnn/start_server.bat b/bird_cnn/start_server.bat new file mode 100644 index 0000000..dc9811c --- /dev/null +++ b/bird_cnn/start_server.bat @@ -0,0 +1 @@ +python -m uvicorn server:app --reload \ No newline at end of file diff --git a/cnn_website/package-lock.json b/cnn_website/package-lock.json index 2fd75b2..314b07e 100644 --- a/cnn_website/package-lock.json +++ b/cnn_website/package-lock.json @@ -9,7 +9,8 @@ "version": "0.0.0", "dependencies": { "react": "^19.2.5", - "react-dom": "^19.2.5" + "react-dom": "^19.2.5", + "react-router-dom": "^7.14.2" }, "devDependencies": { "@eslint/js": "^10.0.1", @@ -264,31 +265,6 @@ "node": ">=6.9.0" } }, - "node_modules/@emnapi/core": { - "version": "1.10.0", - "resolved": "https://registry.npmjs.org/@emnapi/core/-/core-1.10.0.tgz", - "integrity": "sha512-yq6OkJ4p82CAfPl0u9mQebQHKPJkY7WrIuk205cTYnYe+k2Z8YBh11FrbRG/H6ihirqcacOgl2BIO8oyMQLeXw==", - "dev": true, - "license": "MIT", - "optional": true, - "peer": true, - "dependencies": { - "@emnapi/wasi-threads": "1.2.1", - "tslib": "^2.4.0" - } - }, - "node_modules/@emnapi/runtime": { - "version": "1.10.0", - "resolved": "https://registry.npmjs.org/@emnapi/runtime/-/runtime-1.10.0.tgz", - "integrity": "sha512-ewvYlk86xUoGI0zQRNq/mC+16R1QeDlKQy21Ki3oSYXNgLb45GV1P6A0M+/s6nyCuNDqe5VpaY84BzXGwVbwFA==", - "dev": true, - "license": "MIT", - "optional": true, - "peer": true, - "dependencies": { - "tslib": "^2.4.0" - } - }, "node_modules/@emnapi/wasi-threads": { "version": "1.2.1", "resolved": "https://registry.npmjs.org/@emnapi/wasi-threads/-/wasi-threads-1.2.1.tgz", @@ -1056,6 +1032,19 @@ "dev": true, "license": "MIT" }, + "node_modules/cookie": { + "version": "1.1.1", + "resolved": "https://registry.npmjs.org/cookie/-/cookie-1.1.1.tgz", + "integrity": "sha512-ei8Aos7ja0weRpFzJnEA9UHJ/7XQmqglbRwnf2ATjcB9Wq874VKH9kfjjirM6UhU2/E5fFYadylyhFldcqSidQ==", + "license": "MIT", + "engines": { + "node": ">=18" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/express" + } + }, "node_modules/cross-spawn": { "version": "7.0.6", "resolved": "https://registry.npmjs.org/cross-spawn/-/cross-spawn-7.0.6.tgz", @@ -2110,6 +2099,7 @@ "resolved": "https://registry.npmjs.org/react-dom/-/react-dom-19.2.5.tgz", "integrity": "sha512-J5bAZz+DXMMwW/wV3xzKke59Af6CHY7G4uYLN1OvBcKEsWOs4pQExj86BBKamxl/Ik5bx9whOrvBlSDfWzgSag==", "license": "MIT", + "peer": true, "dependencies": { "scheduler": "^0.27.0" }, @@ -2117,6 +2107,44 @@ "react": "^19.2.5" } }, + "node_modules/react-router": { + "version": "7.14.2", + "resolved": "https://registry.npmjs.org/react-router/-/react-router-7.14.2.tgz", + "integrity": "sha512-yCqNne6I8IB6rVCH7XUvlBK7/QKyqypBFGv+8dj4QBFJiiRX+FG7/nkdAvGElyvVZ/HQP5N19wzteuTARXi5Gw==", + "license": "MIT", + "dependencies": { + "cookie": "^1.0.1", + "set-cookie-parser": "^2.6.0" + }, + "engines": { + "node": ">=20.0.0" + }, + "peerDependencies": { + "react": ">=18", + "react-dom": ">=18" + }, + "peerDependenciesMeta": { + "react-dom": { + "optional": true + } + } + }, + "node_modules/react-router-dom": { + "version": "7.14.2", + "resolved": "https://registry.npmjs.org/react-router-dom/-/react-router-dom-7.14.2.tgz", + "integrity": "sha512-YZcM5ES8jJSM+KrJ9BdvHHqlnGTg5tH3sC5ChFRj4inosKctdyzBDhOyyHdGk597q2OT6NTrCA1OvB/YDwfekQ==", + "license": "MIT", + "dependencies": { + "react-router": "7.14.2" + }, + "engines": { + "node": ">=20.0.0" + }, + "peerDependencies": { + "react": ">=18", + "react-dom": ">=18" + } + }, "node_modules/rolldown": { "version": "1.0.0-rc.17", "resolved": "https://registry.npmjs.org/rolldown/-/rolldown-1.0.0-rc.17.tgz", @@ -2174,6 +2202,12 @@ "semver": "bin/semver.js" } }, + "node_modules/set-cookie-parser": { + "version": "2.7.2", + "resolved": "https://registry.npmjs.org/set-cookie-parser/-/set-cookie-parser-2.7.2.tgz", + "integrity": "sha512-oeM1lpU/UvhTxw+g3cIfxXHyJRc/uidd3yK1P242gzHds0udQBYzs3y8j4gCCW+ZJ7ad0yctld8RYO+bdurlvw==", + "license": "MIT" + }, "node_modules/shebang-command": { "version": "2.0.0", "resolved": "https://registry.npmjs.org/shebang-command/-/shebang-command-2.0.0.tgz", diff --git a/cnn_website/package.json b/cnn_website/package.json index 1f2063d..b4d179c 100644 --- a/cnn_website/package.json +++ b/cnn_website/package.json @@ -11,7 +11,8 @@ }, "dependencies": { "react": "^19.2.5", - "react-dom": "^19.2.5" + "react-dom": "^19.2.5", + "react-router-dom": "^7.14.2" }, "devDependencies": { "@eslint/js": "^10.0.1", diff --git a/cnn_website/src/App.jsx b/cnn_website/src/App.jsx index fe2a3fe..0c144e7 100644 --- a/cnn_website/src/App.jsx +++ b/cnn_website/src/App.jsx @@ -1,15 +1,22 @@ import { useState } from 'react' +import { BrowserRouter as Router, Routes, Route } from "react-router-dom"; import reactLogo from './assets/react.svg' import viteLogo from './assets/vite.svg' import heroImg from './assets/hero.png' import './App.css' import Menu from './Menu' +import Homepage from './Homepage'; +import Bird_CNN from './Bird_CNN'; function App() { return ( <> + + } /> + } /> + ); } diff --git a/cnn_website/src/Bird_CNN.css b/cnn_website/src/Bird_CNN.css new file mode 100644 index 0000000..bd17af2 --- /dev/null +++ b/cnn_website/src/Bird_CNN.css @@ -0,0 +1,5 @@ +.content-block { + display: flex; + align-items: baseline; + gap: 20px; +} \ No newline at end of file diff --git a/cnn_website/src/Bird_CNN.jsx b/cnn_website/src/Bird_CNN.jsx new file mode 100644 index 0000000..35575c5 --- /dev/null +++ b/cnn_website/src/Bird_CNN.jsx @@ -0,0 +1,68 @@ +import { useState } from 'react' +import './Bird_CNN.css' + +function Bird_CNN() { + + const [file, setFile] = useState(null); + const [birdClass, setBirdClass] = useState(null); + const [confidence, setConfidence] = useState(null); + const [error, setError] = useState(false); + + const handleImage = (e) => { + setFile(e.target.files[0]); + }; + + const sendImage = async (e) => { + if (!file) return; + + const formData = new FormData(); + formData.append("file", file); + + try { + const response = await fetch("http://127.0.0.1:8000/predict", { + method: "POST", + body: formData, + }); + + if (!response.ok) { + setError(true); + } + else { + setError(false); + } + + const result = await response.json(); + setBirdClass(result["class"]); + const confidence = result["confidence"]; + setConfidence(`${Math.round(confidence * 100)}%`); + } + catch (error) { + console.error("Upload failed:", error); + } + }; + + return ( + <> +

bird-cnn

+
+ + + + +
+ {!error &&
+

Bird Species:

+

{birdClass}

+
} + {!error &&
+

Model Confidence:

+

{confidence}

+
} + {error &&

An Error has uccured. Please try again later.

} +
+
+ + ); +} + +export default Bird_CNN; \ No newline at end of file diff --git a/cnn_website/src/Homepage.jsx b/cnn_website/src/Homepage.jsx new file mode 100644 index 0000000..a490d43 --- /dev/null +++ b/cnn_website/src/Homepage.jsx @@ -0,0 +1,9 @@ +function Homepage() { + return ( + <> +

Homepage

+ + ); +} + +export default Homepage; \ No newline at end of file diff --git a/cnn_website/src/Menu.jsx b/cnn_website/src/Menu.jsx index 8613fa9..2e100eb 100644 --- a/cnn_website/src/Menu.jsx +++ b/cnn_website/src/Menu.jsx @@ -1,15 +1,12 @@ +import { Link } from 'react-router-dom'; import './Menu.css' function Menu() { return ( <> ); diff --git a/cnn_website/src/main.jsx b/cnn_website/src/main.jsx index b9a1a6d..8051dd6 100644 --- a/cnn_website/src/main.jsx +++ b/cnn_website/src/main.jsx @@ -2,9 +2,12 @@ import { StrictMode } from 'react' import { createRoot } from 'react-dom/client' import './index.css' import App from './App.jsx' +import { BrowserRouter } from 'react-router-dom' createRoot(document.getElementById('root')).render( - - , -) + + + + +);