import sys
import json
import threading
import queue
import subprocess
import tkinter as tk
from pathlib import Path
from PIL import Image, ImageDraw, ImageFont, ImageTk

# --- Configuration & Globals ---
padding = 60

# Queue payload: (pil_image, json_path, metadata)
# metadata is a dict: {'copie': str, 'part': int, 'schema': dict}
image_queue = queue.Queue(maxsize=5)

try:
    font = ImageFont.truetype("DejaVuSans.ttf", size=30)
except OSError:
    font = ImageFont.load_default()

# --- Helper Functions (Shared) ---

def page_number(b, nb_pages):
    column_width = 1000 // nb_pages
    center_x = (b[1] + b[3]) // 2
    return center_x // column_width

def convert_box2d(b, pn_ori, npn, tot_ori, tot_dest):
    l = b.copy()
    l[1] = (l[1] - (1000 // tot_ori) * (pn_ori-1)) * tot_ori // tot_dest\
        + (1000 // tot_dest) * (npn - 1)
    l[3] = (l[3] - (1000 // tot_ori) * (pn_ori-1)) * tot_ori // tot_dest\
        + (1000 // tot_dest) * (npn - 1)
    return l

def convert_list(l, group_id, json_schema):
    ll = []
    nb_pages = json_schema["columns_per_file"][group_id-1]
    nb_previous_pages = sum([json_schema["columns_per_file"][i] for i in range(group_id-1)])
    nb_tot_pages = sum([e for e in json_schema["columns_per_file"]])
    for e in l:
        ee = e.copy()
        pn = page_number(e["box_2d"], nb_pages)
        npn = pn + nb_previous_pages
        ee["box_2d"] = convert_box2d(ee["box_2d"], pn, npn, nb_pages, nb_tot_pages)
        ee["part"] = group_id
        ee["pn"] = npn
        ll.append(ee)
    return ll

def prepare_image(image_path: str, bounding_boxes, all_labels, nb_pages):
    im = Image.open(image_path)
    im.load()
    width, height = im.size
    new_im = Image.new(im.mode, (width + padding, height), "white")
    new_im.paste(im, (0, 0))
    draw = ImageDraw.Draw(new_im)
    bounding_boxes.sort(key=lambda b: (page_number(b["box_2d"], nb_pages), b["box_2d"][0]))
    last_label_index = -1

    for bbox in bounding_boxes:
        raw_y_min = int(bbox["box_2d"][0] * height / 1000)
        raw_x_min = int(bbox["box_2d"][1] * width  / 1000)
        raw_y_max = int(bbox["box_2d"][2] * height / 1000)
        raw_x_max = int(bbox["box_2d"][3] * width  / 1000)
        abs_y_min = max(0, raw_y_min - 10)
        abs_x_min = max(0, raw_x_min - 10)
        abs_y_max = min(height, raw_y_max + 10)
        abs_x_max = min(width, raw_x_max + 10)

        color = "black"
        label = bbox.get("label")
        if label and label in all_labels:
            current_index = all_labels.index(label)
            if current_index < last_label_index:
                color = "red"
            last_label_index = current_index

        draw.rectangle(((abs_x_min, abs_y_min), (abs_x_max, abs_y_max)), outline=color, width=4)
        if label:
            if abs_y_min > 80:
                draw.text((abs_x_min + 8, abs_y_min - 30), label, fill=color, font=font)
            else:
                draw.text((abs_x_min + 8, abs_y_max + 6), label, fill=color, font=font)
    return new_im

# --- Processing Logic (Worker Thread) ---

def worker_thread(base_dir, files_to_process, all_labels):
    """
    Iterates through files, prepares VISUALS only, and puts metadata in queue.
    Does NOT write final JSON files anymore.
    """
    for img_path in files_to_process:
        json_path = base_dir / f"{img_path.stem}.json"
        copie_part = int(img_path.stem[-2:])
        copie = img_path.stem[:-3]
        json_schema_path = base_dir / 'Cutleft' / f"{copie}_schema.json"

        try:
            with open(json_schema_path, 'r') as f:
                json_schema = json.load(f)
        except:
            print("No json_schema : ", json_schema_path)
            continue

        nb_pages = json_schema["columns_per_file"][copie_part-1]

        if json_path.exists():
            try:
                # Read strictly for visualization purposes
                with open(json_path, 'r') as f:
                    json_result = json.load(f)

                bb_list = json_result.get("list", [])
                print(f"Buffering {img_path.name}...")

                pil_image = prepare_image(str(img_path), bb_list, all_labels, nb_pages)

                # Package metadata needed for final calculation later
                metadata = {
                    "copie": copie,
                    "part": copie_part,
                    "schema": json_schema,
                    "name": json_result.get("name", "")
                }

                image_queue.put((pil_image, json_path, metadata))
            except Exception as e:
                print(f"Error processing {img_path.name}: {e}")

    # Sentinel to indicate finished
    image_queue.put((None, None, None))

# --- GUI Logic (Main Thread) ---

class ImageViewer:
    def __init__(self, root, base_dir):
        self.root = root
        self.base_dir = base_dir
        self.root.title("Bounding Box Viewer")
        self.label = tk.Label(root, text="Waiting for images...")
        self.label.pack(expand=True, fill="both")

        # Display State
        self.current_image = None
        self.current_json_path = None
        self.current_meta = None # Stores schema/copie info
        self.is_viewing = False
        self.scale_factor = 1.0
        self.orig_size = (1, 1)

        # Data Aggregation State
        self.active_copie_name = None
        self.accumulated_results = None # Dict with "name" and "list"

        # Bindings
        self.root.bind('<Return>', self.on_enter)
        self.root.bind('e', self.on_edit)
        self.root.bind('o', self.on_open_pdf)
        self.root.bind('<Escape>', lambda e: self.root.quit())
        self.label.bind('<Button-1>', self.on_click)

        self.poll_queue()

    def poll_queue(self):
        if not self.is_viewing:
            try:
                pil_image, json_path, metadata = image_queue.get_nowait()

                # Handle End of Stream
                if pil_image is None:
                    self.save_current_batch() # Save any remaining data
                    print("All images processed.")
                    self.root.quit()
                    return

                # Check if we switched to a new "Copie" group
                if self.active_copie_name != metadata["copie"]:
                    self.save_current_batch() # Write previous group to disk
                    # Start new batch
                    self.active_copie_name = metadata["copie"]
                    self.accumulated_results = {"name": metadata["name"], "list": []}

                self.display_image(pil_image, json_path, metadata)
            except queue.Empty:
                pass
        self.root.after(100, self.poll_queue)

    def save_current_batch(self):
        """Writes the accumulated data to the main JSON file."""
        if self.active_copie_name and self.accumulated_results:
            main_json_path = self.base_dir / f"{self.active_copie_name}.json"
            print(f"Writing aggregated result to {main_json_path}")
            with open(main_json_path, 'w') as f:
                json.dump(self.accumulated_results, f)
            self.accumulated_results = None

    def display_image(self, pil_image, json_path, metadata):
        self.orig_size = pil_image.size
        self.scale_factor = 1.0
        screen_h = self.root.winfo_screenheight() - 100
        if pil_image.height > screen_h:
            self.scale_factor = screen_h / pil_image.height
            pil_image = pil_image.resize((int(pil_image.width * self.scale_factor),
                                          int(pil_image.height * self.scale_factor)))

        self.tk_image = ImageTk.PhotoImage(pil_image)
        self.label.config(image=self.tk_image, text=f"Processing: {json_path.name}")
        self.current_json_path = json_path
        self.current_meta = metadata
        self.is_viewing = True
        self.root.lift()

    def on_enter(self, event):
        if self.is_viewing:
            print(f"Committing data for {self.current_json_path.name}...")

            # --- CRITICAL CHANGE: Re-read JSON here to capture user edits ---
            try:
                with open(self.current_json_path, 'r') as f:
                    current_data = json.load(f)

                # Perform the conversion now, post-edit
                converted_items = convert_list(
                    current_data["list"],
                    self.current_meta["part"],
                    self.current_meta["schema"]
                )

                # Add to accumulator
                if self.accumulated_results:
                    self.accumulated_results["list"].extend(converted_items)
                    # Update name just in case (though usually consistent per group)
                    self.accumulated_results["name"] = current_data.get("name", self.accumulated_results["name"])

            except Exception as e:
                print(f"Error re-reading/saving {self.current_json_path}: {e}")

            # Advance UI
            self.is_viewing = False
            self.label.config(image="", text="Loading next...")

    def on_open_pdf(self, event):
        if self.is_viewing and self.current_json_path:
            pdf_path = self.current_json_path.with_suffix(".pdf")
            print(f"Opening {pdf_path}")
            subprocess.Popen(['xdg-open', str(pdf_path)])

    def on_edit(self, event):
        if self.is_viewing and self.current_json_path:
            print(f"Opening {self.current_json_path}")
            subprocess.Popen(['xdg-open', str(self.current_json_path)])

    def on_click(self, event):
        if not self.is_viewing: return
        x = int(event.x / self.scale_factor)
        y = int(event.y / self.scale_factor)
        w, h = self.orig_size
        box = [
            int(max(0, y - 5) / h * 1000),
            int(max(0, x - 5) / (w- padding) * 1000),
            int(min(h, y + 5) / h * 1000),
            int(min(w, x + 5) / (w - padding) * 1000),
        ]
        box_str = "{ \"box_2d\": " + str(box) + ", \"label\": \"\" },"
        print(f"Copied box at ({x},{y}): {box_str}")
        self.root.clipboard_clear()
        self.root.clipboard_append(box_str)

if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python plotting.py <directory_or_file>")
        sys.exit(1)

    input_path = Path(sys.argv[1])
    files_to_process = []

    if input_path.is_file():
        base_dir = input_path.parent
        stem = input_path.stem
        img_path = base_dir / "Cutleft" / f"{stem}.jpg"
        if not img_path.exists() and input_path.parent.name == "Cutleft":
             base_dir = input_path.parent.parent
             img_path = input_path
        if not img_path.exists():
            print(f"Error: Could not find image at {img_path}")
            sys.exit(1)
        files_to_process = [img_path]
    else:
        base_dir = input_path
        cutleft_dir = base_dir / "Cutleft"
        if not cutleft_dir.exists():
            print(f"Error: {cutleft_dir} does not exist.")
            sys.exit(1)
        files_to_process = sorted(cutleft_dir.glob("*.jpg"))

    try:
        all_labels = list(filter(None, (base_dir / "labels").read_text().splitlines()))
    except FileNotFoundError:
        all_labels = []

    t = threading.Thread(target=worker_thread, args=(base_dir, files_to_process, all_labels))
    t.daemon = True
    t.start()

    root = tk.Tk()
    app = ImageViewer(root, base_dir)
    root.mainloop()