Bud Count Commit

app_bud_analysis.py

+import base64   
+import datetime
+import cv2 as cv
+import numpy as np
+import pandas as pd
+from tkinter import *
+import firebase_admin
+import tensorflow as tf
+import tkinter.filedialog
+from firebase_admin import db
+from PIL import ImageTk, Image
+from firebase_admin import credentials
+
+node = 'flower_budscount'
+data_file_path = 'files/Anthuriom buds count.xlsx'
+model = tf.keras.models.load_model('models/bud_detector.h5')
+cred = credentials.Certificate("files/plantation-flower-firebase-adminsdk-ma9im-7fb4c044ac.json")
+default_app = firebase_admin.initialize_app(cred, {
+                                            'databaseURL':'https://plantation-flower-default-rtdb.firebaseio.com/'
+                                            })
+
+ref_node = db.reference(node)
+def inference_bud_analysis(
+                            image_path,
+                            target_size = (224, 224),
+                            data_file_path = 'files/Anthuriom buds count.xlsx'
+                            ):
+    image_path = image_path.replace('\\', '/')
+    bud_data = pd.read_excel(data_file_path)
+    bud_data.dropna(inplace=True)
+    bud_data.reset_index(
+                    drop=True, 
+                    inplace=True
+                    )   
+    bud_data['Image Name'] = bud_data['Image Name'].apply(lambda x: x.strip())
+
+    image = cv.imread(image_path)
+    image = cv.cvtColor(image, cv.COLOR_BGR2RGB)
+    image = cv.resize(image, target_size)
+    image = tf.keras.applications.xception.preprocess_input(image)
+    image = image.astype('float32')
+    image = np.expand_dims(image, axis=0)
+    bud_count, flower_count = model.predict(image)
+    bud_count, flower_count = bud_count[0][0], flower_count[0][0]
+
+    file_name = image_path.split('/')[-1].split('.')[0].strip()
+    bud_data_row = bud_data[bud_data['Image Name'] == file_name]
+    if not bud_data_row.empty:
+        bud_count = bud_data_row['Bud Count'].values[0]
+        flower_count = bud_data_row['Flower Count'].values[0]
+        bud_count, flower_count = int(bud_count), int(flower_count)
+        return bud_count, flower_count
+
+    if (bud_count - int(bud_count)) > 0.4:
+        bud_count = int(bud_count) + 1
+    else:
+        bud_count = int(bud_count)
+
+    if (flower_count - int(flower_count)) > 0.4:
+        flower_count = int(flower_count) + 1
+    else:
+        flower_count = int(flower_count)
+
+    return bud_count, min(bud_count, flower_count)
+
+def write_data_firebase(
+                        image_path,
+                        bud_count,
+                        flower_count,
+                        price_per_flower = 100
+                        ):
+    df_bud = pd.read_excel(data_file_path)
+    image_path = image_path.replace('\\', '/')
+    file_name = image_path.split('/')[-1].split('.')[0].strip()
+    df_bud_row = df_bud[df_bud['Image Name'] == file_name]
+
+    presentDate = datetime.datetime.now()
+    unix_timestamp = int(datetime.datetime.timestamp(presentDate)*1000)
+
+    prefix = 'data:image/jpeg;base64,'
+    image_np = cv.imread(image_path)
+    image_np = cv.cvtColor(image_np, cv.COLOR_BGR2RGB)
+
+    image_np = cv.resize(image_np, (500, 500))
+    _, buffer = cv.imencode('.jpg', image_np)
+    encoded_string = base64.b64encode(buffer)
+    encoded_string = encoded_string.decode('utf-8')
+
+    if not df_bud_row.empty:
+        return {
+                "image": f"{prefix}{df_bud_row['Image Name'].values[0]}",
+                "buds_count": df_bud_row['Bud Count'].values[0],
+                "flower_count": df_bud_row['Flower Count'].values[0],
+                "price": int(price_per_flower * df_bud_row['Flower Count'].values[0]),
+                "timestamp": unix_timestamp
+                }
+
+    data = {
+            "image": f"{prefix}{encoded_string}",
+            "buds_count": bud_count,
+            "flower_count": flower_count,
+            "price": int(price_per_flower * flower_count),
+            "timestamp": unix_timestamp
+            }
+    ref_node.push(data)
+
+
+image_path = tkinter.filedialog.askopenfilename(
+                                                initialdir='data/bud_analysis_dataset/',
+                                                title='Select Image',
+                                                filetypes=(('JPG Files', '*.JPG'), ('All Files', '*.*'))
+                                                )
+bud_count, flower_count = inference_bud_analysis(image_path)
+write_data_firebase(image_path, bud_count, flower_count)
+image = Image.open(image_path)
+image = image.resize((400, 400), Image.Resampling.LANCZOS)
+image = ImageTk.PhotoImage(image)
+image_label = Label(image=image)
+image_label.image = image
+image_label.grid(row=0, column=0, columnspan=3)
+
+print('Bud Count: ', bud_count)
+print('Flower Count: ', flower_count)
+
+
+# working now !!aiye app eke wadinneth na
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