changed website structure, added new cnn files

bird_cnn/r-cnn.py

@@ -0,0 +1,51 @@
+import torch
+import torch.nn as nn
+import torchvision
+from torchvision import datasets, transforms
+from torch.utils.data import DataLoader, random_split
+import matplotlib.pyplot as plt
+
+from bird_cnn import Bird_CNN, sample, trainCNN
+
+from enum import Enum
+
+from PIL import Image
+
+SAVE_PATH = "./saved_models"
+IMAGE_SIZE = 64
+
+class bird_species(Enum):
+    Common_Kingfisher = 0
+    CommonMyna = 1
+    House_Crow = 2
+    Indian_Peacock = 3
+    Indian_Pitta = 4
+    Ruddy_Shelduck = 5
+    Sarus_Crane = 6
+
+transform = transforms.Compose([
+    transforms.Resize(IMAGE_SIZE),
+    transforms.CenterCrop(IMAGE_SIZE),
+    transforms.ToTensor()
+])
+
+dataset = datasets.ImageFolder("data/train", transform=transform)
+
+train_size = int(0.8 * len(dataset))
+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)
+
+
+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=32, c_out=7)
+model.to(device)
+optimizer = torch.optim.Adam(model.parameters(), lr=1e-3, weight_decay=1e-4)
+loss_module = nn.CrossEntropyLoss()
+
+trainCNN(model, optimizer, loss_module, train_loader, val_loader, device, 50, SAVE_PATH=SAVE_PATH, save=True)

bird_cnn/selective_search.py

@@ -0,0 +1,85 @@
+from collections import defaultdict
+from enum import Enum
+import os
+
+import numpy as np
+import matplotlib.pyplot as plt
+import cv2
+
+import torch
+from torchvision import transforms
+import torch.nn.functional as F
+
+from bird_cnn import Bird_CNN
+
+from PIL import Image
+
+
+
+BUILD_PATH = "./build_models"
+IMAGE_SIZE = 64
+
+class bird_species(Enum):
+    Common_Kingfisher = 0
+    CommonMyna = 1
+    House_Crow = 2
+    Indian_Peacock = 3
+    Indian_Pitta = 4
+    Ruddy_Shelduck = 5
+    Sarus_Crane = 6
+
+transform = transforms.Compose([
+    transforms.Resize(IMAGE_SIZE),
+    transforms.CenterCrop(IMAGE_SIZE),
+    transforms.ToTensor()
+])
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+model = Bird_CNN(c_in=3, c_hidden=16, c_out=7)
+full_path = os.path.join(BUILD_PATH, "bird_cnn")
+model.load_state_dict(torch.load(full_path, map_location=torch.device(device)))
+model.to(device)
+model.eval()
+
+img = cv2.imread("./testimages/two_crows.jpg")
+
+if img is None:
+    raise ValueError("Image not found or path is wrong")
+
+ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()
+ss.setBaseImage(img)
+
+ss.switchToSelectiveSearchFast()
+rects = ss.process()
+
+# convert to array for easy sorting
+rects = np.array(rects)
+
+# compute area
+areas = rects[:, 2] * rects[:, 3]
+
+# sort by area (descending)
+idx = np.argsort(-areas)
+
+# take top 10
+top10 = rects[idx[:200]]
+class_conf_sum = defaultdict(float)
+
+for (x, y, w, h) in top10:
+    #cv2.rectangle(img_copy, (x, y), (x + w, y + h), (0, 255, 0), 1)
+    crop = img[y:y+h, x:x+w]
+    crop_pil = Image.fromarray(cv2.cvtColor(crop, cv2.COLOR_BGR2RGB))
+    image = transform(crop_pil).unsqueeze(0).to(device)
+
+    with torch.no_grad():
+        pred = model(image)
+        probs = F.softmax(pred, dim=1)
+        confidence, cls = torch.max(probs, dim=1)
+        if confidence.item() < 0.7:
+            continue
+
+        class_conf_sum[cls.item()] += confidence.item()
+
+for i in range(6):
+    print(str(i) + ": " + str(class_conf_sum[i]))

cnn_website/src/Bird_CNN.css

@@ -1,3 +1,7 @@
+.button-div {
+    height: 40px;
+}
+
 .custom-button {
     font-size: 1rem;
     font-weight: bold;
@@ -27,11 +31,10 @@
 }
 
 #site-headline {
-    margin-left: 100px;
+    margin: 50px min(100px, 10vw) 50px min(100px, 10vw);
-    margin-bottom: 50px;
     color: rgb(47, 168, 208);
     font-weight: bold;
-    font-size: 4rem;
+    font-size: clamp(1rem, 8vw, 4rem);
     position: relative;
     width: fit-content;
 }
@@ -67,12 +70,13 @@ a:hover {
     flex-wrap: wrap;
     overflow: hidden;
     border-radius: 12px;
-    margin: 180px 50px 50px 50px;
+    margin: 50px 50px 50px 50px;
 }
 
 .image-box {
-    height: 400px;
+    height: fit-content;
     margin-top: 40px;
+    margin-bottom: 40px;
     display: flex;
     align-items: center;
     justify-content: center;
@@ -86,7 +90,10 @@ a:hover {
     cursor: pointer;
     border: 2px solid black;
     border-Radius: 10px;
-
+    user-select: none;
+    height: auto;
+    max-height: 400px;
+    max-width: min(700px, 80vw);
 }
 
 .image-box img:hover {
@@ -95,15 +102,27 @@ a:hover {
 
 .content-block {
     display: flex;
+    justify-content: center;
     align-items: center;
-    gap: 20px;
+    flex-wrap: wrap;
-    height: 40px;
+    column-gap: 20px;
+    height: fit-content;
+    width: fit-content;
+}
+
+.loader-container {
+    scroll-margin-top: 100px;
+    width: 85px;
+    height: 35px;
+    display: flex;
+    justify-content: center;
+    padding: 20px 0px 20px 0px;
 }
 
 /* HTML: <div class="loader"></div> */
 .loader {
-    width: 85px;
+    width: 100%;
-    height: 25px;
+    height: 100%;
     --g1: conic-gradient(from 90deg at left 3px top 3px, #0000 90deg, #fff 0);
     --g2: conic-gradient(from -90deg at bottom 3px right 3px, #0000 90deg, #fff 0);
     background: var(--g1), var(--g1), var(--g1), var(--g2), var(--g2), var(--g2);
@@ -137,3 +156,51 @@ a:hover {
         background-size: 25px 100%, 25px 100%, 25px 100%
     }
 }
+
+.site-box {
+    margin-top: 150px;
+    width: 100%;
+}
+
+.request-box {
+    height: fit-content;
+    width: min(700px, 80%);
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    flex: 0 0 auto;
+    margin: 0px 50px 0px 50px;
+}
+
+.request-box * {
+    box-sizing: content-box;
+}
+
+.input-box {
+    scroll-margin-top: 100px;
+    width: min(500px, 100%);
+    height: 160px;
+    display: flex;
+    justify-content: space-evenly;
+    align-items: center;
+    flex-wrap: wrap;
+    gap: 20px;
+}
+
+.response-block {
+    width: 80%;
+    height: 100px;
+    margin: 40px;
+    display: flex;
+    flex-direction: column;
+    align-items: flex-start;
+    justify-content: center;
+    gap: 40px;
+}
+
+.conten-block-text {
+    display: flex;
+    flex-direction: column;
+    justify-content: center;
+    margin: 0;
+}

cnn_website/src/Bird_CNN.jsx

@@ -85,7 +85,7 @@ function Bird_CNN() {
 
     return (
         <>
-            <div className='site-box' style={{ marginTop: "150px" }}>
+            <div className='site-box'>
                 <h1 id='site-headline'>Bird Species Expert</h1>
                 <div className='content-box' style={{ display: "flex", flexWrap: "wrap", justifyContent: "center" }}>
                     <div className='explanation-box left'>
@@ -93,15 +93,15 @@ function Bird_CNN() {
                         <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>
                     </div>
 
-                    <div className='request-box' style={{ height: "800px", width: "700px", display: "flex", flexDirection: "column", alignItems: "center", flex: "0 0 auto", margin: "100px 50px 0px 50px" }}>
+                    <div className='request-box'>
-                        <div ref={scrollRefUploadButton} className='input-box' style={{ scrollMarginTop: "100px", marginBottom: "80px", width: "500px", height: "40px", display: "flex", justifyContent: "space-evenly", alignItems: "center" }}>
+                        <div ref={scrollRefUploadButton} className='input-box'>
-                            <div>
+                            <div className='button-div'>
                                 <input disabled={loading} ref={fileInputRef} type="file" id='fileUpload' accept="image/jpeg" onChange={handleImage} style={{ display: "none" }} />
                                 <label htmlFor="fileUpload" className="custom-button">
                                     Select Image
                                 </label>
                             </div>
-                            <div>
+                            <div className='button-div'>
                                 <button id='button-send' onClick={sendImage} style={{ display: "none" }} disabled={loading} />
                                 <label htmlFor="button-send" className="custom-button inactive" ref={uploadButton}>
                                     Ask Expert
@@ -116,25 +116,24 @@ function Bird_CNN() {
                                 disabled={loading}
                                 src={preview}
                                 alt="preview"
-                                style={{ height: "100%", userSelect: "none", maxWidth: "700px" }}
                             />
                         </div>
 
-                        <div ref={scrollRefClassifiction} style={{ scrollMarginTop: "100px", paddingTop: "10px", marginTop: "30px", width: "85px", height: "35px", display: "flex", justifyContent: "center", minHeight: "25px", minWidth: "85px" }}>
+                        <div ref={scrollRefClassifiction} className='loader-container'>
                             {loading && <div className='loader'></div>}
                         </div>
 
 
-                        <div className='response-block' style={{ marginTop: "40px", width: "80%", margin: "40px", display: "flex", flexDirection: "column", alignItems: "flex-start", gap: "10px" }}>
+                        <div className='response-block'>
                             <div className='content-block class'>
-                                <h3>Bird Species: </h3>
+                                <h3 className='conten-block-text'>Bird Species: </h3>
-                                <p id='bird-class-text'>{birdClass}</p>
+                                <p id='bird-class-text' className='conten-block-text'>{birdClass}</p>
                             </div>
                             <div className='content-block confidence'>
-                                <h4>Model Confidence: </h4>
+                                <h4 className='conten-block-text'>Model Confidence: </h4>
-                                <p id='bird-confidence-text'>{confidence}</p>
+                                <p id='bird-confidence-text' className='conten-block-text'>{confidence}</p>
                             </div>
-                            {error && <h4>An Error has uccured. Please try again later.</h4>}
+                            {error && <h4 className='conten-block-text'>An Error has uccured. Please try again later.</h4>}
                         </div>
                     </div>