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+FROM python:3.11-slim
+WORKDIR /webapp
+COPY . .
+RUN pip install --upgrade pip
+RUN pip install --no-cache-dir -r requirements.txt
+CMD ["gunicorn", "-b", "0.0.0.0:7860", "--timeout", "120", "app:app"]
+EXPOSE 7860

app.py

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+import os
+from flask import Flask, render_template, request
+from flask_cors import cross_origin, CORS
+import tensorflow.lite as lite
+from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
+from utils.make_upload_dir import make_upload_dir
+from tensorflow.keras.utils import load_img, save_img, img_to_array
+from numpy import array, round
+from utils.delete_file import delete_file
+from requests import get
+
+
+app = Flask(__name__, template_folder='templates', static_folder='static')
+CORS(app)
+
+CLASS_INDICES = {'Bean': 0,
+                 'Bitter_Gourd': 1,
+                 'Bottle_Gourd': 2,
+                 'Brinjal': 3,
+                 'Broccoli': 4,
+                 'Cabbage': 5,
+                 'Capsicum': 6,
+                 'Carrot': 7,
+                 'Cauliflower': 8,
+                 'Cucumber': 9,
+                 'Papaya': 10,
+                 'Potato': 11,
+                 'Pumpkin': 12,
+                 'Radish': 13,
+                 'Tomato': 14}
+
+interpreter = lite.Interpreter(model_path=os.path.join("models", "vegetable_classification_model_mnet.tflite"))
+
+
+def predict(test_image):
+    interpreter.allocate_tensors()
+
+    input_details = interpreter.get_input_details()[0]
+    output_details = interpreter.get_output_details()[0]
+
+    test_image = test_image.astype(input_details["dtype"])
+    interpreter.set_tensor(input_details["index"], test_image)
+    interpreter.invoke()
+    output = interpreter.get_tensor(output_details["index"])[0]
+
+    prediction = [*CLASS_INDICES.keys()][output.argmax()]
+    probability = round(output.max() * 100, 2)
+    result = f'{prediction} ({probability}%)'
+    return result
+
+
+@app.route("/")
+@cross_origin()
+def index():
+    """
+    displays the index.html page
+    """
+    display_image = os.path.join("static", "white.png")
+    delete_file(os.path.join('.', 'static', 'uploads'))
+    delete_file(os.path.join('.', 'static', 'output', 'display.jpg'))
+    return render_template("index.html", display_image=display_image)
+
+
+@app.route("/", methods=["POST"])
+@cross_origin()
+def file_prediction():
+    upload_file_path = ""
+    result = ''
+    error = ""
+    try:
+        upload_file_path = os.path.join('.', 'static', 'uploads')
+        make_upload_dir(upload_file_path)
+        upload_filename = "input.jpg"
+        upload_file_path = os.path.join(upload_file_path, upload_filename)
+
+        file_url = request.form['fileinput']
+        headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36'}
+        r = get(file_url, headers=headers)
+        with open(upload_file_path, "wb") as file:
+            file.write(r.content)
+
+        test_image = load_img(upload_file_path, color_mode="rgb", target_size=(224, 224))
+        test_image = img_to_array(test_image)
+        test_image = preprocess_input(test_image)
+        test_image = array([test_image])
+
+        display_image = os.path.join('.', 'static', 'output', 'display.jpg')
+        save_img(path=display_image, x=test_image[0])
+
+        result = predict(test_image)
+        delete_file(upload_file_path)
+
+    except Exception as e:
+        # raise
+        result = ''
+        error = e
+        display_image = os.path.join("static", "white.png")
+        delete_file(upload_file_path)
+
+    return render_template("index.html", result=result, error=error, display_image=display_image)
+
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5002)

models/vegetable_classification_model_mnet.tflite

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+version https://git-lfs.github.com/spec/v1
+oid sha256:646ea12cef64a1b4bca597811ec7c21b6f7da0eb6ff4d567207e165184e2dffb
+size 21413256

requirements.txt

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+tensorflow-cpu==2.12.0
+numpy==1.22.4
+flask==2.2.2
+flask_cors==3.0.10
+gunicorn==20.1.0
+Pillow==9.5.0
+requests==2.30.0

static/styles.css

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+ html, body {
+      min-height: 100%;
+      }
+      body, div, form, input, select, p {
+      padding: 0;
+      margin: 0;
+      outline: none;
+      font-family: Roboto, Arial, sans-serif;
+      font-size: 14px;
+      color: #666;
+      line-height: 22px;
+      }
+      h1 {
+      position: absolute;
+      margin: 0;
+      font-size: 28px;
+      color: #fff;
+      z-index: 2;
+      }
+      h2 {
+      font-weight: 400;
+      }
+      .testbox {
+      display: flex;
+      justify-content: center;
+      align-items: center;
+      height: inherit;
+      padding: 20px;
+      }
+      .testbox1 {
+      display: flex;
+      justify-content: center;
+      align-items: center;
+      height: inherit;
+      padding: 5px;
+      }
+      form {
+      width: 30%;
+      padding: 20px;
+      border-radius: 6px;
+      background: #fff;
+      box-shadow: 0 0 20px 0 #095484;
+      }
+      .banner {
+      position: relative;
+      height: 80px;
+      background-size: cover;
+      display: flex;
+      justify-content: center;
+      align-items: center;
+      text-align: center;
+      }
+
+      .banner::after {
+      content: "";
+      background-color: rgba(0, 0, 0, 0.4);
+      position: absolute;
+      width: 100%;
+      height: 100%;
+      }
+      input, select {
+      margin-bottom: 2px;
+      border: 1px solid #ccc;
+      border-radius: 3px;
+      }
+      input {
+      width: calc(100% - 10px);
+      padding: 5px;
+      }
+      select {
+      width: 100%;
+      padding: 7px 0;
+      background: transparent;
+      }
+      .item:hover p, .item:hover i, .question:hover p, .question label:hover, input:hover::placeholder, a {
+      color: #095484;
+      }
+      .item input:hover, .item select:hover {
+      border: 1px solid transparent;
+      box-shadow: 0 0 6px 0 #095484;
+      color: #095484;
+      }
+      .item {
+      position: relative;
+      margin: 10px 0;
+      }
+
+
+      .btn-block {
+      margin-top: 10px;
+      text-align: center;
+      }
+      button {
+      width: 150px;
+      padding: 10px;
+      border: none;
+      border-radius: 5px;
+      background: #095484;
+      font-size: 16px;
+      color: #fff;
+      cursor: pointer;
+      }
+      button:hover {
+      background: #0666a3;
+      }
+      ul {
+  list-style-type: none;
+  margin: 0;
+  padding: 0;
+  overflow: hidden;
+  background-color: #333;
+}
+
+li {
+  float: left;
+}
+
+li a {
+  display: block;
+  color: white;
+  text-align: center;
+  padding: 14px 16px;
+  text-decoration: none;
+}
+
+/* Change the link color to #111 (black) on hover */
+li a:hover {
+  background-color: #111;
+
+li {
+  border-right: 1px solid #bbb;
+}
+
+li:last-child {
+  border-right: none;
+}

templates/index.html

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+<!--sourced and modified from https://www.w3docs.com/learn-html/html-form-templates.html -->
+<!DOCTYPE html>
+<html>
+  <head>
+    <title>Vegetable Classifier</title>
+    <link href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700" rel="stylesheet">
+    <link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.5.0/css/all.css" integrity="sha384-B4dIYHKNBt8Bc12p+WXckhzcICo0wtJAoU8YZTY5qE0Id1GSseTk6S+L3BlXeVIU" crossorigin="anonymous">
+    <link rel="stylesheet" href="static/styles.css">
+  </head>
+  <body>
+    <div class="testbox">
+      <form action="/" method="POST" enctype="multipart/form-data">
+        <div class="banner">
+          <h1>Vegetable Classifier</h1>
+        </div>
+          <h5>Detectable Vegetables: Broad Bean, Bitter Gourd, Bottle Gourd, Green Round Brinjal, Broccoli, Cabbage, Capsicum, Carrot,
+              Cauliflower, Cucumber, Raw Papaya, Potato, Green Pumpkin, Radish, Tomato</h5>
+        <h5>The model is trained on <a href="https://www.kaggle.com/datasets/misrakahmed/vegetable-image-dataset" target="_blank">images</a> clicked using a mobile phone camera.</h5>
+<p>Please paste the image URL of a vegetable<sup style="color: red;">*</sup></p>
+          <div class="item">
+
+          <input type="text" name="fileinput" id="fileinput" autocomplete="off" required/>
+              </div>
+
+
+        <div class="btn-block">
+          <button type="submit" href="/file_input">Submit</button>
+        </div>
+<div class="item">
+          <p style="color: red;">{{error}}</p>
+</div>
+      </form>
+
+    </div>
+<div class="testbox1">
+             {{result}}
+            </div>
+  <div class="testbox1">
+             <img src={{display_image}} />
+            </div>
+
+
+  </body>
+</html>

utils/delete_file.py

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+from os import path
+from shutil import rmtree
+
+
+def delete_file(path_: str):
+    if path.exists(path_):
+        rmtree(path=path_, ignore_errors=True)

utils/make_upload_dir.py

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+from os import path, makedirs
+from shutil import rmtree
+
+
+def make_upload_dir(path_: str):
+    if path.exists(path_):
+        rmtree(path=path_, ignore_errors=True)
+    makedirs(path_)