Upload 9 files

Browse files

Files changed (10) hide show

.gitattributes +1 -0
app.py +49 -0
app.txt +0 -0
models/EfficentEnt_unfreezing.h5 +3 -0
models/EfficientNet_Unfreezing.h5 +3 -0
models/EfficientNet_keras.keras +3 -0
models/model.pkl +3 -0
models/model_efficientNet_unfreezing.h5 +3 -0
templates/index.html +147 -0
templates/index.txt +0 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+models/EfficientNet_keras.keras filter=lfs diff=lfs merge=lfs -text

app.py ADDED Viewed

	@@ -0,0 +1,49 @@

+from flask import Flask, request, jsonify, render_template
+import numpy as np
+import pandas as pd
+import tensorflow as tf
+from efficientnet.tfkeras import EfficientNetB0
+from tensorflow.keras.layers import Dense, GlobalAveragePooling2D
+from tensorflow.keras.models import Model
+import pickle
+import cv2
+app = Flask(__name__)
+# Load the saved model
+model_path = "C://Users//ritik//Downloads//emotion detection//models//EfficientNet_Unfreezing.h5"
+model = tf.keras.models.load_model(model_path)
+# Preprocess image function
+def preprocess_image(image):
+    gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
+    if len(gray_image.shape) < 3:
+        return cv2.cvtColor(gray_image, cv2.COLOR_GRAY2RGB)
+    blurred_image = cv2.GaussianBlur(gray_image, (5, 5), 0)
+    equalized_image = cv2.equalizeHist(blurred_image)
+    _, thresholded_image = cv2.threshold(equalized_image, 127, 255, cv2.THRESH_BINARY)
+    final_image = cv2.cvtColor(thresholded_image, cv2.COLOR_GRAY2RGB)
+    return final_image
+# Prediction route
+@app.route('/predict', methods=['POST'])
+def predict():
+    file = request.files['image']
+    img = cv2.imdecode(np.fromstring(file.read(), np.uint8), cv2.IMREAD_COLOR)
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    img = cv2.resize(img, (224, 224))  # Ensure image size matches the input size of the model
+    img = preprocess_image(img)
+    img = img / 255.0
+    img = np.expand_dims(img, axis=0)
+    prediction = model.predict(img)
+    emotions = ['Angry', 'Happy', 'Neutral', 'Sad', 'Surprise']
+    result = emotions[np.argmax(prediction)]
+    return jsonify({'emotion': result})
+# Home route
+@app.route('/')
+def index():
+    return render_template('index.html')
+if __name__ == '__main__':
+    app.run(debug=True)

app.txt ADDED Viewed

File without changes

models/EfficentEnt_unfreezing.h5 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:bdfd6ee5ab70bb428a00516c51b1429ece1f8e46fe31e419eda15823129f70d5
+size 65198840

models/EfficientNet_Unfreezing.h5 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:7ac16764ccc615089c8a7b204df6fde6573e04ade1080f7d442332ba27a5c4fe
+size 65186536

models/EfficientNet_keras.keras ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:828c5de91dfbd6ee1fb6dbaa052c653ed630ca55570809a0d2830e2bcf4d1224
+size 64960178

models/model.pkl ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:48834423069e906cc91a6f388e176ced0b3869c1755d17932dec9ed12a29dca5
+size 64960277

models/model_efficientNet_unfreezing.h5 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:7ac16764ccc615089c8a7b204df6fde6573e04ade1080f7d442332ba27a5c4fe
+size 65186536

templates/index.html ADDED Viewed

	@@ -0,0 +1,147 @@

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Emotion Detection</title>
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            margin: 0;
+            padding: 0;
+            background-color: #f0f0f0;
+            text-align: center;
+        }
+        h1 {
+            margin-top: 30px;
+            color: #333;
+        }
+        #upload-form {
+            margin-top: 20px;
+        }
+        #result {
+            margin-top: 20px;
+            font-weight: bold;
+        }
+        #result.emotion-happy {
+            color: #00cc00;
+        }
+        #result.emotion-sad {
+            color: #3333ff;
+        }
+        #result.emotion-angry {
+            color: #cc0000;
+        }
+        #result.emotion-neutral {
+            color: #666666;
+        }
+        #result.emotion-surprise {
+            color: #ff9900;
+        }
+        input[type="file"] {
+            display: none;
+        }
+        .custom-file-upload {
+            display: inline-block;
+            padding: 10px 20px;
+            cursor: pointer;
+            background-color: #4CAF50;
+            color: white;
+            border-radius: 5px;
+            transition: background-color 0.3s;
+        }
+        .custom-file-upload:hover {
+            background-color: #45a049;
+        }
+        #uploaded-image {
+            margin-top: 20px;
+            max-width: 400px;
+            border-radius: 5px;
+        }
+        #upload-button {
+            display: none;
+        }
+        #reset-button {
+            margin-top: 20px;
+            padding: 10px 20px;
+            background-color: #f44336;
+            color: white;
+            border: none;
+            border-radius: 5px;
+            cursor: pointer;
+            transition: background-color 0.3s;
+        }
+        #reset-button:hover {
+            background-color: #d32f2f;
+        }
+    </style>
+</head>
+<body>
+    <h1>Emotion Detection</h1>
+    <form id="upload-form" enctype="multipart/form-data">
+        <label for="image" class="custom-file-upload">
+            Choose File
+        </label>
+        <input type="file" id="image" name="image" accept="image/*" required>
+        <button id="upload-button" type="submit">Upload Image</button>
+    </form>
+    <div id="result"></div>
+    <img id="uploaded-image" src="#" alt="Uploaded Image">
+    <button id="reset-button">Reset</button>
+    <script>
+        document.getElementById('image').addEventListener('change', function(event) {
+            var fileInput = event.target;
+            var file = fileInput.files[0];
+            var uploadedImage = document.getElementById('uploaded-image');
+            var uploadButton = document.getElementById('upload-button');
+            if (file) {
+                uploadedImage.src = URL.createObjectURL(file);
+                uploadButton.style.display = 'inline-block';
+            } else {
+                uploadedImage.src = '#';
+                uploadButton.style.display = 'none';
+            }
+        });
+        document.getElementById('upload-form').addEventListener('submit', function(event) {
+            event.preventDefault();
+            var formData = new FormData(this);
+            fetch('/predict', {
+                method: 'POST',
+                body: formData
+            })
+            .then(response => {
+                if (!response.ok) {
+                    throw new Error('Network response was not ok');
+                }
+                return response.json();
+            })
+            .then(data => {
+                var resultDiv = document.getElementById('result');
+                resultDiv.innerText = 'Detected Emotion: ' + data.emotion;
+                resultDiv.className = 'emotion-' + data.emotion.toLowerCase();
+            })
+            .catch(error => {
+                var resultDiv = document.getElementById('result');
+                resultDiv.innerText = 'Error: ' + error.message;
+                resultDiv.className = '';
+            });
+        });
+        document.getElementById('reset-button').addEventListener('click', function(event) {
+            var form = document.getElementById('upload-form');
+            form.reset();
+            var uploadedImage = document.getElementById('uploaded-image');
+            uploadedImage.src = '#';
+            var resultDiv = document.getElementById('result');
+            resultDiv.innerText = '';
+            resultDiv.className = '';
+            var uploadButton = document.getElementById('upload-button');
+            uploadButton.style.display = 'none';
+        });
+    </script>
+</body>
+</html>

templates/index.txt ADDED Viewed

File without changes