from flask import Flask, request, jsonify
import cv2
import numpy as np
import pytesseract
import matplotlib.pyplot as plt
from PIL import Image
import os
# from google.colab import files

app = Flask(__name__)


@app.route('/', methods=['GET'])
def hello():
    pesan = request.args.get('pesan')
    return jsonify({'response': 'Hello, Flask! '+pesan})


@app.route('/test-form', methods=['POST'])
def test_form():
    nama = request.form['nama']
    return jsonify({'response': f'Halo, {nama}!'})


@app.route('/test-form-image', methods=['POST'])
def test_form_image():
    # image = request.form['image']
    # all_data = {**request.args.to_dict(), **request.form.to_dict(),
    #             **request.files.to_dict()}
    # return jsonify(request.files)
    if 'image' in request.files:
        uploaded_file = request.files['image']
        # Melihat informasi tentang file
        # print(f"File Name: {uploaded_file.filename}")
        # print(f"Content Type: {uploaded_file.content_type}")
        if uploaded_file.filename == '':
            return 'No selected file'

        # Mendapatkan lokasi dari file Python yang sedang berjalan
        current_directory = os.path.dirname(os.path.abspath(__file__))
        uploaded_file.save(os.path.join(
            current_directory, uploaded_file.filename))

        return 'File berhasil diunggah dan disimpan!'
        # Anda dapat melakukan operasi lain di sini dengan file yang diunggah
        # Misalnya, menyimpannya ke sistem file dengan:
        # uploaded_file.save('lokasi_direktori_dan_nama_file_yang_diinginkan')
        # return 'File berhasil diunggah!'
    else:
        return 'Tidak ada file yang diunggah!'


@app.route('/process-image', methods=['POST'])
def process_image():
    if 'image' in request.files:
        uploaded_file = request.files['image']
        if uploaded_file.filename == '':
            return 'Tidak ada File yang dipih'

        current_directory = os.path.dirname(os.path.abspath(__file__))
        uploaded_file.save(os.path.join(
            current_directory, uploaded_file.filename))
    else:
        return 'Tidak ada file yang diunggah!'

    try:
        if uploaded_file is not None:
            # Lakukan proses pada data gambar, misalnya menggunakan OpenCV
            # Simpan hasil dalam variabel `result`

            # Membaca gambar dengan OpenCV
            image = open(uploaded_file.filename, "rb")
            image_data = image.read()
            image_array = bytearray(image_data)
            nparr = np.frombuffer(image_array, np.uint8)
            img_cv2 = cv2.imdecode(nparr, cv2.IMREAD_COLOR)

            # read img
            gray = cv2.cvtColor(img_cv2, cv2.COLOR_BGR2GRAY)

            # (2) Threshold
            th, threshed = cv2.threshold(gray, 127, 255, cv2.THRESH_TRUNC)

            # (3) Detect
            result = pytesseract.image_to_string((threshed), lang="ind")

            hasil = result.split("\n")

            # (5) Normalize
            for word in result.split("\n"):
                if "”—" in word:
                    word = word.replace("”—", ":")

                # normalize NIK
                if "NIK" in word:
                    nik_char = word.split()
                    if "D" in word:
                        word = word.replace("D", "0")
                    if "?" in word:
                        word = word.replace("?", "7")

            # print(word)
            return jsonify({'status': 'Berhasil', 'result': hasil})
        else:
            return jsonify({'error': 'No image uploaded'})

        # return jsonify(word)
    except Exception as e:
        return jsonify(error=str(e))


if __name__ == '__main__':
    app.run(host='localhost', port=8888, debug=False)

# image = open("R.jpeg", "rb")

# image_data = image.read()
# image_array = bytearray(image_data)
# nparr = np.frombuffer(image_array, np.uint8)
# img_cv2 = cv2.imdecode(nparr, cv2.IMREAD_COLOR)

# # read img
# gray = cv2.cvtColor(img_cv2, cv2.COLOR_BGR2GRAY)

# # (2) Threshold
# th, threshed = cv2.threshold(gray, 127, 255, cv2.THRESH_TRUNC)

# # (3) Detect
# result = pytesseract.image_to_string((threshed), lang="ind")
# print(result)
# # (5) Normalize
# for word in result.split("\n"):
#     if "”—" in word:
#         word = word.replace("”—", ":")

#     # normalize NIK
#     if "NIK" in word:
#         nik_char = word.split()
#         if "D" in word:
#             word = word.replace("D", "0")
#         if "?" in word:
#             word = word.replace("?", "7")

# print(word)