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marvin
2026-05-11 04:19:50 +02:00
parent 7bd32f49ee
commit 19f639d168
5 changed files with 117 additions and 91 deletions
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api/train_bird.py
+1 -1
View File
@@ -16,7 +16,7 @@ IMAGE_SIZE = 64
class bird_species(Enum):
Common_Kingfisher = 0
CommonMyna = 1
Common_Myna = 1
House_Crow = 2
Indian_Peacock = 3
Indian_Pitta = 4
website/package-lock.json
Generated
+87 -87
View File
@@ -21,7 +21,7 @@
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@@ -2362,7 +2362,7 @@
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website/package.json
+1 -1
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@@ -23,6 +23,6 @@
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website/src/Bird_CNN.css
+17
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@@ -50,6 +50,23 @@
background: rgb(47, 168, 208);
}
.species-item {
list-style: none;
position: relative;
}
.species-item::before {
content: "";
position: absolute;
left: -16px;
top: 50%;
height: 1.5px;
width: 10px;
background: rgb(255, 255, 255);
border-radius: 8px;
transform: translateY(-50%);
}
.site-box a {
text-decoration: none;
border-bottom: 1px solid rgb(255, 255, 255);
website/src/Bird_CNN.jsx
+11 -2
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@@ -90,7 +90,16 @@ function Bird_CNN() {
<div className='content-box' style={{ display: "flex", flexWrap: "wrap", justifyContent: "center" }}>
<div className='explanation-box left'>
<h2 style={{ color: "rgb(47, 168, 208)" }}>Explanation</h2>
<span>Select an image and upload it to our bird expert. You will receive a classification and how certain the expert is with her opinion. Be aware that the expert may not be always right.</span>
<span>Select and upload an image to our bird classification model. The system will return a predicted species along with a confidence score indicating how certain the model is about its prediction. Please note that the model may not always produce correct classifications. The supported Species are:</span>
<ul className='species-list'>
<li className='species-item'>Common Kingfisher</li>
<li className='species-item'>Common Myna</li>
<li className='species-item'>House Crow</li>
<li className='species-item'>Indian Peacock</li>
<li className='species-item'>Indian Pitta</li>
<li className='species-item'>Ruddy Shelduck</li>
<li className='species-item'>Sarus Crane</li>
</ul>
</div>
<div className='request-box'>
@@ -140,7 +149,7 @@ function Bird_CNN() {
<div className='explanation-box right'>
<h3>Model Architecture</h3>
<div style={{ display: "inline" }}>
<span>The model used for classification is a convolutional neural network. The model uses who knows how many layers, a dropout and multiple batchnormalsation.</span>
<span>The classification model is based on a convolutional neural network (CNN). The architecture consists of eight skip blocks, each containing three convolutional layers, followed by batch normalization after each convolution and a dropout rate of 0.3. The dataset comprised seven classes, with 1,200 images per class.</span>
</div>
</div>
</div>