import os, math, csv from collections import defaultdict import tkinter as tk from tkinter import scrolledtext, messagebox, IntVar, Frame, Label from PIL import Image, ImageTk import googlemaps """ Potential improvements: - Use a database to store the batch information (e.g. SQLite) - Use JSON instead of CSV for storing batch information - Automatically update Google Sheets / Excel Online with the category and notes - Use a more sophisticated clustering algorithm (e.g. DBSCAN) to group images together - Use a more sophisticated GUI library (e.g. PyQt) for a more polished interface - Use library for calculating distances between coordinates (e.g. geopy) """ # Extracts iemit number for the filename. def get_iemit(filename): parts = filename.split("_") return parts[1] # Extracts latitude and longitude from the filename. def get_coordinates(filename): parts = filename.split("_") latitude = float(parts[3]) longitude = float(parts[5]) return latitude, longitude # Haversine distance def calculate_distance_hav(lat1, lon1, lat2, lon2): # Convert latitude and longitude from degrees to radians lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2]) # Haversine formula dlat = lat2 - lat1 dlon = lon2 - lon1 a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2 c = 2 * math.asin(math.sqrt(a)) r = 6371 # Radius of Earth in kilometers. Use 3956 for miles return c * r # Euclidean distance def calculate_distance(lat1, lon1, lat2, lon2): return math.sqrt((lat1 - lat2)**2 + (lon1 - lon2)**2) # Batches images together based on their proximity in latitude and longitude with a given tolerance. # Returns: key(latitude, longitude) : value(list of filenames) # Potnetial improvement: generate new filenames for each batch # Potential improvement: DBSCAN clustering def batch_images(image_folder, tolerance=0.1): batches = defaultdict(list) centers = [] for filename in os.listdir(image_folder): if filename.endswith(".png"): latitude, longitude = get_coordinates(filename) found_batch = False for center in centers: center_lat, center_lon = center if calculate_distance(latitude, longitude, center_lat, center_lon) < tolerance: batches[center].append(filename) found_batch = True break if not found_batch: # Create a new batch with this image as its center new_center = (latitude, longitude) centers.append(new_center) batches[new_center].append(filename) return batches def find_batch(filename, batches): for center, filenames in batches.items(): if filename in filenames: return center, filenames return None def read_processed_batches(csv_file_path): processed_batches = set() if os.path.exists(csv_file_path): with open(csv_file_path, mode='r', newline='', encoding='utf-8-sig') as csvfile: reader = csv.DictReader(csvfile) for row in reader: # Assuming 'batch_id' is the column that contains the unique identifier processed_batches.add(row['batch_id']) return processed_batches gmaps = googlemaps.Client(key='AIzaSyBnMCEpxGUxTpGKx0qAXXEbbBpUfhtJSPQ') image_folder = "../emit_images" tolerance = 0.15 batches = batch_images(image_folder, tolerance) csv_file_name = "EMIT_labelled.csv" class BatchDisplayGUI: def __init__(self, master, batches): self.csv_file = open(csv_file_name, 'a', newline='', encoding='utf-8') self.csv_writer = csv.writer(self.csv_file) self.master = master self.batches = batches self.current_batch_index = 0 self.current_image_index = 0 self.image_labels = {} self.is_closing = False print(f"Number of batches left: {len(batches)}") self.setup_widgets() self.display_batch_info() self.master.protocol("WM_DELETE_WINDOW", self.on_window_close) def setup_widgets(self): categories = ["upstream", "midstream", "downstream", "landfill", "mine", "others","?"] # Create a frame for the navigation buttons nav_frame = tk.Frame(self.master) nav_frame.grid(row=4, column=1, sticky="ew", padx=5) # Create a frame for the inputs on the right side input_frame = tk.Frame(self.master) input_frame.grid(row=0, column=2, rowspan=4, sticky="nsew", padx=10, pady=10) # Configure the grid layout self.master.grid_columnconfigure(0, weight=1) self.master.grid_columnconfigure(1, weight=1) self.master.grid_columnconfigure(2, weight=1) # Text area on the left side self.text_area = scrolledtext.ScrolledText(self.master, wrap=tk.WORD, width=20, height=15) self.text_area.grid(row=0, column=0, rowspan=4, padx=10, pady=10, sticky="nsew") self.text_area.config(state=tk.DISABLED) # Frame for image in the middle self.image_frame = Frame(self.master, width=200, height=200) # Assuming fixed size for demonstration self.image_frame.grid(row=0, column=1, rowspan=4, padx=10, pady=10, sticky="nsew") # Inputs on the right side tk.Label(input_frame, text="Category:").grid(row=0, column=0, sticky="e", padx=5) self.category_entry = tk.StringVar() # Variable to hold the selected category self.category_entry.set(categories[6]) # Set default value self.category_menu = tk.OptionMenu(input_frame, self.category_entry, *categories) self.category_menu.grid(row=0, column=1, sticky="ew", padx=5) tk.Label(input_frame, text="Notes:").grid(row=1, column=0, sticky="e", padx=5) self.notes_entry = tk.Entry(input_frame) self.notes_entry.grid(row=1, column=1, sticky="ew", padx=5) self.emitter_var = tk.IntVar() tk.Checkbutton(input_frame, text="Emitter Present", variable=self.emitter_var).grid(row=2, column=0, columnspan=2, sticky="w", padx=5) # Navigation buttons self.prev_button = tk.Button(nav_frame, text="Previous Image", command=self.show_prev_image) self.prev_button.grid(row=0, column=0, sticky="ew", padx=5) self.next_image_button = tk.Button(nav_frame, text="Next Image", command=self.show_next_image) self.next_image_button.grid(row=0, column=1, sticky="ew", padx=5) self.next_batch_button = tk.Button(self.master, text="Next Batch", command=self.update_csv) self.next_batch_button.grid(row=5, column=1, sticky="ew", padx=5, pady=5) # Adjust the row configuration to make the text area and image frame expand to fill the space vertically self.master.grid_rowconfigure(0, weight=1) self.master.grid_rowconfigure(1, weight=1) self.master.grid_rowconfigure(2, weight=1) self.master.grid_rowconfigure(3, weight=1) nav_frame.columnconfigure(0, weight=1) nav_frame.columnconfigure(1, weight=1) input_frame.grid_columnconfigure(1, weight=1) def display_image(self, filename): # Clear previous images for widget in self.image_frame.winfo_children(): widget.destroy() print(f"Displaying image: {get_iemit(filename)}") image = Image.open(os.path.join(image_folder, filename)) image = image.resize((750, 550), Image.Resampling.LANCZOS) photo = ImageTk.PhotoImage(image) label = Label(self.image_frame, image=photo) label.image = photo label.pack() def show_next_image(self): self.save_current_label() self.current_image_index = min(len(batches[self.batches[self.current_batch_index]]) - 1, self.current_image_index + 1) filenames = batches[self.batches[self.current_batch_index]] filename = filenames[self.current_image_index] # Save previous input notes, emitter_present = self.image_labels.get(filename, ["", ""]) if notes: self.notes_entry.insert(0, notes) else: self.notes_entry.delete(0, tk.END) self.emitter_var.set(1 if emitter_present == "yes" else 0) self.display_image(filename) def show_prev_image(self): self.save_current_label() self.current_image_index = max(0, self.current_image_index - 1) filenames = batches[self.batches[self.current_batch_index]] filename = filenames[self.current_image_index] # Save previous input notes, emitter_present = self.image_labels.get(filename, ["", ""]) if notes: self.notes_entry.insert(0, notes) else: self.notes_entry.delete(0, tk.END) self.emitter_var.set(1 if emitter_present == "yes" else 0) self.display_image(filename) def save_current_label(self): current_image = batches[self.batches[self.current_batch_index]][self.current_image_index] notes = self.notes_entry.get() emitter_present = "yes" if self.emitter_var.get() else "no" self.image_labels[current_image] = [notes, emitter_present] def update_csv(self): if self.is_closing: return center = self.batches[self.current_batch_index] # iterate through the batch IDs (center coordinates) filenames = batches.get(center) # get the filenames for the corresponding batch ID (center coordinates) # Grab inputs from the user category = self.category_entry.get() for filename in filenames: notes, emitter_present = self.image_labels.get(filename, ["", ""]) self.csv_writer.writerow([center, filename, category, notes, emitter_present]) # Clear the entry fields self.category_entry.set("?") self.notes_entry.delete(0, tk.END) self.emitter_var.set(0) self.current_batch_index += 1 self.current_image_index = 0 # Display the next batch self.display_batch_info() def display_batch_info(self): if self.is_closing: return print(f"Current batch index: {self.current_batch_index}") if self.current_batch_index >= len(self.batches): self.text_area.delete(1.0, tk.END) self.text_area.insert(tk.INSERT, "No more batches to display.") messagebox.showinfo("No More Batches", "No more batches to display.") return center = self.batches[self.current_batch_index] # iterate through the batch IDs (center coordinates) filenames = batches.get(center) # get the filenames for the corresponding batch ID (center coordinates) # Perform a nearby search places_result = gmaps.places_nearby(location=(center[0], center[1]), radius=1000, open_now=False) # Display the next batch if self.current_batch_index < len(self.batches): self.text_area.config(state=tk.NORMAL) self.text_area.delete(1.0, tk.END) self.text_area.insert(tk.INSERT, f"Batch centered at {center}:\n") for filename in filenames: filename = get_iemit(filename) self.text_area.insert(tk.INSERT, f"\t- {filename}\n") self.text_area.insert(tk.INSERT, "\nNearby places:\n") for place in places_result['results']: types = place.get('types', []) types_str = ', '.join(types) # Join the list of types into a comma-separated string self.text_area.insert(tk.INSERT, f"\t- {place['name']} (Types: {types_str})\n") self.text_area.config(state=tk.DISABLED) # Start by displaying the first image in the batch self.display_image(filenames[0]) def on_window_close(self): print("Window is closing") self.is_closing = True self.csv_file.close() self.master.destroy() def main(): window = tk.Tk() window.title("Batch Information") unprocessed_batches = set(batches.keys()) processed_batches = read_processed_batches(csv_file_name) # Remove processed batches from the set of unprocessed batches unprocessed_batches = [batch for batch in unprocessed_batches if str(batch) not in processed_batches] gui = BatchDisplayGUI(window, unprocessed_batches) window.mainloop() if __name__ == "__main__": main() # Print information about a specific batch # image_folder = "../small" # tolerance = 0.15 # batches = batch_images(image_folder, tolerance) # center, filenames = find_batch("iemit_980_lat_38.8503652059909_lon_54.23517605482166_DT_20230620084414.png", batches) # print(f"Batch centered at {center}:") # sorted_filenames = sorted(filenames, key=lambda x: int(get_iemit(x))) # for filename in sorted_filenames: # print(f"\t- {get_iemit(filename)}") # Print information about the batches # for center, filenames in batches.items(): # print(f"Batch centered at ({center[0]}, {center[1]}):") # for filename in filenames: # print(f"\t- {filename}") #print(f"Number of batches: {len(batches)}") # Export batches to a CSV file # with open('batches.csv', 'w', newline='') as csvfile: # writer = csv.writer(csvfile) # writer.writerow(['Center Latitude', 'Center Longitude', 'Filename']) # for center, filenames in batches.items(): # for filename in filenames: # writer.writerow([center[0], center[1], filename])