app.py

import gradio as gr
import random
import openpyxl
from openpyxl.styles import Font, Alignment
import tempfile
from roboflow import Roboflow
from PIL import Image
import cv2
import numpy as np
import os
# import dw
from gradio_calendar import Calendar
import datetime

excel_tempfile_state = gr.State()
roll_number_state = gr.State()
sno_state = gr.State()
roll_number_state.value=1
sno_state.value=1

str_nums = {"zero":0,"one":1,"two":2,"three":3,"four":4,"five":5,"six":6,"seven":7,"eight":8,"nine":9}

def task1(Examination, Date_Of_Exam, Program, Branch, Course, Name_Of_Faculty, Academic_Year):
  with tempfile.NamedTemporaryFile(suffix=".xlsx", delete=False) as temp_file:
        workbook = openpyxl.Workbook()
        sheet = workbook.active
  # Define font styles
  font_size_20 = Font(name="Times New Roman", size=20, bold=True)
  font_size_18 = Font(name="Times New Roman", size=18, bold=True)
  font_size_16 = Font(name="Times New Roman", size=16, bold=True)
  font_size_12_bold = Font(name="Times New Roman", size=12, bold=True)

  # Define alignment
  alignment_center = Alignment(horizontal="center")

  # Merge cells for first two rows
  sheet.merge_cells('A1:P1')
  sheet.merge_cells('A2:P2')
  sheet['A1'].value = "LAKIREDDY BALI REDDY COLLEGE OF ENGINEERING"
  sheet['A2'].value = "(AUTONOMOUS)"
  sheet['A1'].font = font_size_20
  sheet['A2'].font = font_size_20
  sheet['A1'].alignment = alignment_center
  sheet['A2'].alignment = alignment_center

  # Merge cells for third row
  sheet.merge_cells('A3:P3')
  sheet['A3'].value = "DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING"
  sheet['A3'].font = font_size_18
  sheet['A3'].alignment = alignment_center

  # Merge cells for fourth row
  sheet.merge_cells('A4:P4')
  sheet['A4'].value = "MID DESCRIPTIVE MARKS LIST"
  sheet['A4'].font = font_size_16
  sheet['A4'].alignment = alignment_center

  # Merge cells for fifth row
  sheet.merge_cells('A5:H5')
  sheet.merge_cells('I5:P5')
  sheet['A5'].value = f"Examination       : {Examination}"
  sheet['I5'].value = f"Date of Exam      : {Date_Of_Exam}"
  sheet['A5'].font = font_size_12_bold
  sheet['I5'].font = font_size_12_bold

  # Merge cells for sixth row
  sheet.merge_cells('A6:H6')
  sheet.merge_cells('I6:P6')
  sheet['A6'].value = f"Program              : {Program}"
  sheet['I6'].value = f"Branch                : {Branch}"
  sheet['A6'].font = font_size_12_bold
  sheet['I6'].font = font_size_12_bold

  # Merge cells for seventh row
  sheet.merge_cells('A7:H7')
  sheet.merge_cells('I7:P7')
  sheet['A7'].value = f"Course                : {Course}"
  sheet['I7'].value = "Maximum Marks : 15"
  sheet['A7'].font = font_size_12_bold
  sheet['I7'].font = font_size_12_bold

  # Merge cells for eighth row
  sheet.merge_cells('A8:H8')
  sheet.merge_cells('I8:P8')
  sheet['A8'].value = f"Name of the Faculty: {Name_Of_Faculty}"
  sheet['I8'].value = f"Academic Year    : {Academic_Year}"
  sheet['A8'].font = font_size_12_bold
  sheet['I8'].font = font_size_12_bold


  ##part two


  # Merge cells for SNo
  sheet.merge_cells('A9:A10')
  sheet['A9'] = "SNo"
  sheet['A9'].font = font_size_12_bold
  sheet['A9'].alignment = alignment_center

  # Add data for Regd Num
  sheet.merge_cells('B9:B10')
  sheet['B9'] = "Regd Num"
  sheet['B9'].font = font_size_12_bold
  sheet['B9'].alignment = alignment_center

  # Add data for Q. No 1
  sheet.merge_cells('C9:F9')
  sheet['C9'] = "Q. No 1"
  sheet['C9'].font = font_size_12_bold
  sheet['C9'].alignment = alignment_center
  sheet['C10'] = "A"
  sheet['C10'].font = font_size_12_bold
  sheet['C10'].alignment = alignment_center
  sheet['D10'] = "B"
  sheet['D10'].font = font_size_12_bold
  sheet['D10'].alignment = alignment_center
  sheet['E10'] = "C"
  sheet['E10'].font = font_size_12_bold
  sheet['E10'].alignment = alignment_center
  sheet['F10'] = "D"
  sheet['F10'].font = font_size_12_bold
  sheet['F10'].alignment = alignment_center

  # Add data for Q. No 2
  sheet.merge_cells('G9:J9')
  sheet['G9'] = "Q. No 2"
  sheet['G9'].font = font_size_12_bold
  sheet['G9'].alignment = alignment_center
  sheet['G10'] = "A"
  sheet['G10'].font = font_size_12_bold
  sheet['G10'].alignment = alignment_center
  sheet['H10'] = "B"
  sheet['H10'].font = font_size_12_bold
  sheet['H10'].alignment = alignment_center
  sheet['I10'] = "C"
  sheet['I10'].font = font_size_12_bold
  sheet['I10'].alignment = alignment_center
  sheet['J10'] = "D"
  sheet['J10'].font = font_size_12_bold
  sheet['J10'].alignment = alignment_center

  # Add data for Q. No 3
  sheet.merge_cells('K9:N9')
  sheet['K9'] = "Q. No 3"
  sheet['K9'].font = font_size_12_bold
  sheet['K9'].alignment = alignment_center
  sheet['K10'] = "A"
  sheet['K10'].font = font_size_12_bold
  sheet['K10'].alignment = alignment_center
  sheet['L10'] = "B"
  sheet['L10'].font = font_size_12_bold
  sheet['L10'].alignment = alignment_center
  sheet['M10'] = "C"
  sheet['M10'].font = font_size_12_bold
  sheet['M10'].alignment = alignment_center
  sheet['N10'] = "D"
  sheet['N10'].font = font_size_12_bold
  sheet['N10'].alignment = alignment_center

  # Add data for Total(30M)
  sheet.merge_cells('O9:O10')
  sheet['O9'] = "Total(30M)"
  sheet['O9'].font = font_size_12_bold
  sheet['O9'].alignment = alignment_center

  # Add data for (Total 15 M)
  sheet.merge_cells('P9:P10')
  sheet['P9'] = "(Total 15 M)"
  sheet['P9'].font = font_size_12_bold
  sheet['P9'].alignment = alignment_center
  workbook.save(temp_file.name)
  excel_tempfile_state.value = temp_file.name
  print(excel_tempfile_state.value)
  return temp_file.name




#configuring interface 1
inputs = [
    gr.Dropdown(["I Mid","II Mid"], value=["I Mid", "II Mid"], label="Examination"),
    Calendar(type="date", label="Date Of Examination"),
    gr.Dropdown(["B-Tech R20","M-Tech R20","MBA R20","B-Tech R17","M-Tech R17","MBA-R17"], value=["B-Tech R20","M-Tech R20","MBA R20","B-Tech R17","M-Tech R17","MBA-R17"], label="Program"),
    gr.Dropdown(["ASE","AI&DS","Civil","CSE","CSE(AI&ML)","ECE","EEE","IT","MECH","MBA"], value=["ASE","AI&DS","Civil","CSE","CSE(AI&ML)","ECE","EEE","IT","MECH","MBA"], label="Branch"),
    gr.components.Textbox(label="Course"),
    gr.components.Textbox(label="Name Of Faculty"),
    gr.components.Textbox(label="Academic Year"),
]
# interface one
iface1 = gr.Interface(
    fn=task1,
    inputs=inputs,
    outputs="file",
    title="Automating Examination Mark Entry with Deep Learning"
)


def predict_and_crop(image_np, api_key, project_name, model_version, confidence=40, overlap=30):
    img = Image.fromarray(image_np)
    rf = Roboflow(api_key=api_key)
    project = rf.workspace().project(project_name)
    print(f"Project: {project}")
    
    model = project.version(model_version).model
    print(f"Model: {model}")

    if model is None:
        raise ValueError(f"Model version {model_version} not found in project {project_name}.")

    corners = model.predict(image_np, confidence=confidence, overlap=overlap).json()
    predictions = corners["predictions"][0]
    prediction = {key: int(value) for key, value in predictions.items() if key in ['x', 'y', 'width', 'height']}
    x1 = int(prediction['x'] - prediction['width'] / 2)
    y1 = int(prediction['y'] - prediction['height'] / 2)
    x2 = int(prediction['x'] + prediction['width'] / 2)
    y2 = int(prediction['y'] + prediction['height'] / 2)
    cropped_img = img.crop((x1, y1, x2, y2))
    cropped_img_np = np.array(cropped_img)
    h, w, c = cropped_img_np.shape
    if h > w:
        cropped_img_np = cv2.rotate(cropped_img_np, cv2.ROTATE_90_CLOCKWISE)
    return cropped_img_np, img


# Function to resize and insert cropped image
def resize_and_insert(cropped_image, output_image_path):
    # base_image = cv2.imread(base_image_path)
    base_height, base_width = (460, 1158)
    base_aspect_ratio = base_width / base_height
    new_width = int(base_height * base_aspect_ratio)
    resized_cropped_img = cv2.resize(cropped_image, (new_width, base_height))
    return resized_cropped_img

# Function to convert string to integer based on confidence level
def convert_str_int(var, conf):
    if conf < 0.5:
        return " "
    else:
        return str_nums[var]

def append_to_workbook(cells_data, excel_file_path):
    workbook = openpyxl.load_workbook(excel_file_path)
    sheet = workbook.active

    # Retrieve current SNo and roll number from state
    sno = sno_state.value
    rno = roll_number_state.value
    if rno<10:
      rno_str = "21761A420"+str(rno)
    else:
      rno_str = "21761A42"+str(rno)
    # Increment SNo and roll number
    sno_state.value = sno + 1
    roll_number_state.value = rno + 1

    next_row = sheet.max_row + 1

    # Insert roll number and SNo
    sheet.cell(row=next_row, column=1, value=sno)
    sheet.cell(row=next_row, column=2, value=rno_str)
    for col, value in enumerate(cells_data, start=3):
        sheet.cell(row=next_row, column=col, value=value)
    marks=[]
    for i in cells_data:
      if str(i).isdigit():
        marks.append(int(i))
      else:
        marks.append(0)
    total_30_marks = max(sum(marks[0:2]),sum(marks[2:4]))+max(sum(marks[4:6]),sum(marks[6:8]))+max(sum(marks[8:10]),sum(marks[10:12]))
    total_15_marks = round(total_30_marks / 2, 2)
    sheet.cell(row=next_row, column=15, value=total_30_marks)
    sheet.cell(row=next_row, column=16, value=total_15_marks)
    # Save the workbook
    workbook.save(excel_file_path)







#All Functions for interface 2
def task2(image_np):
  api_key = "UyAumhQJOJpo7vUu3LaK"
  project_name = "marks_table_detection_lbrce"
  model_version = 1
  base_image_path = "base_img.png"
  temp_image_path = "temp_image.jpg"
  output_image_path = "merged_image.jpg"

  #API and requirements for OCR Model
  rf = Roboflow(api_key="XsMt3y86MNDGihOYcWDY")
  project = rf.workspace().project("mnist-cjkff")
  model = project.version(2).model
  print(f"Model: {model}")

  # Predict and crop
  cropped_image, original_image = predict_and_crop(image_np, api_key, project_name, model_version)

  # Resize and insert
  result_image = resize_and_insert(cropped_image, output_image_path)

  # Cell coordinates
  cell_coordinates = cell_coordinates = [(235, 129), (475, 223), (496, 125), (685, 225), (708, 127), (896, 225), (919, 125), (1140, 217), (232, 253), (473, 346), (500, 249), (687, 347), (708, 250), (896, 346), (920, 249), (1142, 345), (232, 375), (474, 442), (496, 371), (686, 442), (708, 373), (897, 444), (922, 373), (1147, 443)]
  cells_data = [4,5,'','','','',3,2,1,2,'','']
  # qno = 0

  # for i in range(0, len(cell_coordinates), 2):
  #     top_left = cell_coordinates[i]
  #     bottom_right = cell_coordinates[i + 1]
  #     cell = result_image[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]]
  #     cell_gray = cv2.cvtColor(cell, cv2.COLOR_BGR2GRAY)
  #     _, thresholded_cell = cv2.threshold(cell_gray, 127, 255, cv2.THRESH_BINARY_INV)

  #     _, temp_thresholded_path = tempfile.mkstemp(suffix=".jpg")
  #     cv2.imwrite(temp_thresholded_path, thresholded_cell)

  #     res = model.predict(temp_thresholded_path).json()
  #     var = res["predictions"][0]["predictions"][0]["class"]
  #     conf = res["predictions"][0]["predictions"][0]["confidence"]
  #     cells_data.append(convert_str_int(var, conf))
  #     qno += 1
  excel_file_path = excel_tempfile_state.value
  append_to_workbook(cells_data,excel_file_path)
  print(cells_data)
  return cropped_image, cells_data, excel_file_path


iface2 = gr.Interface(
    fn=task2,
    elem_id="my-interface",
    inputs=[
        gr.components.Image(type="numpy", label="Upload Image")
    ],
    outputs=[
        gr.components.Image(type="numpy", label="Cropped Image"),
        gr.components.Textbox(label="Detected Marks"),
        gr.components.File(label="marks_sheet")
    ],
    # examples=[['IMG_20240215_210403.jpg'],['IMG_20240215_210530.jpg'],['IMG_20240215_210534.jpg'],['IMG_20240215_210611.jpg']],
    title="Automating Examination Mark Entry with Deep Learning",
    theme="huggingface"
)
demo = gr.TabbedInterface([iface1, iface2], ["Configure Excel Sheet Data", "Extract marks from Answer Sheets"])

# Run the interface
demo.launch(share=True,debug=True)