#!/usr/bin/env python3
"""
Sign Language Gloss Q&A System
User inputs gloss, system generates corresponding pose video
"""

import torch
from PIL import Image
import numpy as np
import json
import os
import sys
import argparse
from pathlib import Path
import cv2
from tqdm import tqdm
import re

from easy_dwpose import DWposeDetector
from easy_dwpose.draw.controlnext import draw_pose, process_pose_data

# Fixed configuration
DATABASE_PATH = "output/merge/merged_database.npz"  # Database file path
MAPPING_FILE = "output/gloss_mapping.json"  # Mapping file path
OUTPUT_DIR = "output/video"  # Output video directory


class SignLanguageQA:
    def __init__(self):
        self.data = None
        self.metadata = None
        self.gloss_mapping = None
        self.load_database()
        self.load_mapping()

    def load_database(self):
        """Load database"""
        try:
            if not Path(DATABASE_PATH).exists():
                print(f"❌ Database file does not exist: {DATABASE_PATH}")
                print("   Please ensure merge_all_to_database.py has been run to generate database file")
                sys.exit(1)

            print(f"📚 Loading database: {DATABASE_PATH}")
            self.data = np.load(DATABASE_PATH, allow_pickle=True)
            self.metadata = self.data['_metadata'].item()

            print(f"✅ Database loaded successfully!")
            print(f"   📊 Total frames: {self.metadata['total_frames']}")
            print(f"   🎬 Video count: {self.metadata['video_count']}")

        except Exception as e:
            print(f"❌ Database loading failed: {e}")
            sys.exit(1)

    def load_mapping(self):
        """Load gloss mapping file"""
        if Path(MAPPING_FILE).exists():
            try:
                with open(MAPPING_FILE, 'r', encoding='utf-8') as f:
                    self.gloss_mapping = json.load(f)
                print(f"✅ Mapping file loaded successfully: {MAPPING_FILE}")
                print(f"   📝 Contains {len(self.gloss_mapping)} gloss mappings")
            except Exception as e:
                print(f"⚠️  Mapping file loading failed: {e}")
                self.gloss_mapping = None
        else:
            print(f"ℹ️  Mapping file does not exist: {MAPPING_FILE}")
            print("   Will use intelligent matching mode")
            self.gloss_mapping = None

    def find_gloss_videos(self, gloss):
        """Find corresponding video_ids based on a single gloss"""
        if self.gloss_mapping and gloss.upper() in self.gloss_mapping:
            # Use mapping file
            video_ids = self.gloss_mapping[gloss.upper()]
            if not isinstance(video_ids, list):
                video_ids = [video_ids]
            return video_ids
        else:
            # Intelligent matching mode
            gloss_upper = gloss.upper()
            matched_videos = []

            for video_id in self.metadata['video_index'].keys():
                # Multiple matching strategies
                if (gloss_upper == video_id.upper() or
                        gloss_upper in video_id.upper() or
                        video_id.upper().endswith(f"_{gloss_upper}") or
                        video_id.upper().startswith(f"{gloss_upper}_") or
                        f"_{gloss_upper}_" in video_id.upper()):
                    matched_videos.append(video_id)

            return matched_videos

    def get_frames_for_glosses(self, gloss_list, one_video_per_gloss=True):
        """Get all frames corresponding to gloss list

        Args:
            gloss_list: gloss list
            one_video_per_gloss: whether to select only one video per gloss
        """
        all_frame_groups = []  # Frames grouped by gloss
        video_info = []

        for gloss in gloss_list:
            matched_videos = self.find_gloss_videos(gloss)

            if matched_videos:
                print(f"🎯 '{gloss}' -> Found {len(matched_videos)} videos")

                # If selecting only one video, find the first valid one (existing in database)
                videos_to_use = []
                if one_video_per_gloss:
                    # Find the first video that exists in the database
                    for video_id in matched_videos:
                        if video_id in self.metadata['video_index']:
                            videos_to_use = [video_id]
                            if len(matched_videos) > 1:
                                print(f"   💡 Selecting first valid video: {video_id}, skipping other {len(matched_videos) - 1}")
                            break

                    if not videos_to_use:
                        print(f"   ❌ No valid videos found (all video_ids not in database)")
                        continue
                else:
                    videos_to_use = matched_videos

                gloss_frames = []  # All frames for current gloss
                for video_id in videos_to_use:
                    if video_id in self.metadata['video_index']:
                        start_frame = self.metadata['video_index'][video_id]['start_frame']
                        end_frame = self.metadata['video_index'][video_id]['end_frame']
                        frames = list(range(start_frame, end_frame + 1))
                        gloss_frames.extend(frames)
                        video_info.append({
                            'gloss': gloss,
                            'video_id': video_id,
                            'start_frame': start_frame,
                            'end_frame': end_frame,
                            'frame_count': len(frames)
                        })
                        print(f"   📹 {video_id}: {len(frames)} frames ({start_frame}-{end_frame})")
                    else:
                        print(f"   ⚠️  {video_id}: Not found in database")

                if gloss_frames:
                    all_frame_groups.append(gloss_frames)
            else:
                print(f"❌ '{gloss}' -> No matching videos found")
                self.suggest_similar_glosses(gloss)

        # Concatenate frames from all glosses in order
        all_frames = []
        for frame_group in all_frame_groups:
            all_frames.extend(frame_group)

        return all_frames, video_info

    def suggest_similar_glosses(self, gloss):
        """Provide similar suggestions for unfound gloss"""
        gloss_upper = gloss.upper()
        similar_videos = []

        # Find video_id containing partial characters
        for video_id in self.metadata['video_index'].keys():
            score = 0
            for char in gloss_upper:
                if char in video_id.upper():
                    score += 1

            if score >= len(gloss_upper) * 0.5:  # At least 50% character match
                similar_videos.append(video_id)

        if similar_videos:
            print(f"   💡 Similar video_ids: {similar_videos[:5]}")

        # If mapping file exists, show available glosses
        if self.gloss_mapping:
            available_glosses = list(self.gloss_mapping.keys())
            similar_glosses = [g for g in available_glosses if
                               any(char in g for char in gloss_upper)]
            if similar_glosses:
                print(f"   💡 Similar glosses: {similar_glosses[:5]}")

    def create_pose_frame(self, frame_data, width=480, height=480):
        """Create single frame pose image"""
        try:
            processed_pred = process_pose_data(frame_data, height, width)

            vis_img = draw_pose(
                pose=processed_pred,
                H=height,
                W=width,
                include_body=True,
                include_hand=True,
                include_face=True
            )

            return vis_img.transpose(1, 2, 0)

        except Exception as e:
            print(f"⚠️  Failed to create pose frame: {e}")
            return None

    def generate_video(self, frame_indices, output_path, video_info, fps=30, width=480, height=480,
                       smoothing_frames=5, smoothing_method='none'):
        """Generate pose video

        Args:
            frame_indices: frame index list
            output_path: output path
            video_info: video info list
            fps: frame rate
            width: width
            height: height
            smoothing_frames: number of smoothing transition frames
            smoothing_method: smoothing method ('fade', 'blend', 'pause', 'none')
        """
        if not frame_indices:
            return False

        # Create output directory
        output_path.parent.mkdir(parents=True, exist_ok=True)

        # Set video encoder
        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        video_writer = cv2.VideoWriter(str(output_path), fourcc, fps, (width, height))

        if not video_writer.isOpened():
            print("❌ Unable to create video file")
            return False

        original_keys = self.metadata['original_keys']
        successful_frames = 0

        print(f"🎬 Generating video (smoothing method: {smoothing_method})...")

        # Generate pose frames grouped by gloss
        all_pose_frame_groups = []

        print("🔄 Rendering pose frames...")
        current_frame_idx = 0

        for info in video_info:
            gloss_frames = []
            frame_count = info['frame_count']

            for _ in range(frame_count):
                if current_frame_idx < len(frame_indices):
                    frame_idx = frame_indices[current_frame_idx]
                    frame_key = f"frame_{frame_idx:08d}"
                    frame_data = {}

                    for key in original_keys:
                        combined_key = f"{frame_key}_{key}"
                        if combined_key in self.data:
                            frame_data[key] = self.data[combined_key]

                    if frame_data:
                        pose_frame = self.create_pose_frame(frame_data, width, height)
                        if pose_frame is not None:
                            gloss_frames.append(pose_frame)

                    current_frame_idx += 1

            if gloss_frames:
                all_pose_frame_groups.append(gloss_frames)
                print(f"   ✅ {info['gloss']}: {len(gloss_frames)} frames")

        if not all_pose_frame_groups:
            print("❌ No frames generated successfully")
            video_writer.release()
            return False

        # Apply smoothing
        if smoothing_method != 'none' and len(all_pose_frame_groups) > 1:
            final_frames = self.apply_group_smoothing(all_pose_frame_groups, smoothing_frames, smoothing_method)
        else:
            # Directly concatenate all frames
            final_frames = []
            for group in all_pose_frame_groups:
                final_frames.extend(group)

        # Write video
        print("💾 Writing video file...")
        for pose_frame in tqdm(final_frames, desc="Writing frames"):
            pose_frame_bgr = cv2.cvtColor(pose_frame, cv2.COLOR_RGB2BGR)
            video_writer.write(pose_frame_bgr)
            successful_frames += 1

        video_writer.release()

        if successful_frames > 0:
            print(f"✅ Video generated successfully!")
            print(f"   📁 File: {output_path}")
            print(f"   📊 {successful_frames} frames, {fps}fps, {width}x{height}")
            if output_path.exists():
                print(f"   💾 Size: {output_path.stat().st_size / 1024 / 1024:.2f} MB")
            return True
        else:
            print(f"❌ Video generation failed")
            return False

    def apply_group_smoothing(self, frame_groups, smoothing_frames, method):
        """Apply smoothing transition effects to gloss groups"""
        if len(frame_groups) <= 1 or smoothing_frames <= 0:
            final_frames = []
            for group in frame_groups:
                final_frames.extend(group)
            return final_frames

        print(f"🌊 Applying {method} smoothing transition ({smoothing_frames} frames)...")

        if method == 'fade':
            return self.apply_group_fade_smoothing(frame_groups, smoothing_frames)
        elif method == 'blend':
            return self.apply_group_blend_smoothing(frame_groups, smoothing_frames)
        elif method == 'pause':
            return self.apply_group_pause_smoothing(frame_groups, smoothing_frames)
        else:
            final_frames = []
            for group in frame_groups:
                final_frames.extend(group)
            return final_frames

    def apply_group_fade_smoothing(self, frame_groups, fade_frames):
        """Apply fade in/out smoothing to gloss groups"""
        smoothed_frames = []

        for i, group in enumerate(frame_groups):
            if i == 0:
                # First group: fade in
                for f in range(fade_frames):
                    alpha = f / fade_frames
                    black_frame = np.zeros_like(group[0])
                    faded_frame = (black_frame * (1 - alpha) + group[0] * alpha).astype(np.uint8)
                    smoothed_frames.append(faded_frame)

            # Add all frames from current group
            smoothed_frames.extend(group)

            if i < len(frame_groups) - 1:
                # Inter-group transition: fade from last frame of current group to first frame of next group
                next_group = frame_groups[i + 1]
                current_last = group[-1]
                next_first = next_group[0]

                for f in range(fade_frames):
                    alpha = f / fade_frames
                    blended_frame = (current_last * (1 - alpha) + next_first * alpha).astype(np.uint8)
                    smoothed_frames.append(blended_frame)

        return smoothed_frames

    def apply_group_blend_smoothing(self, frame_groups, blend_frames):
        """Apply blend smoothing to gloss groups"""
        smoothed_frames = []

        for i, group in enumerate(frame_groups):
            smoothed_frames.extend(group)

            if i < len(frame_groups) - 1:
                next_group = frame_groups[i + 1]
                current_last = group[-1]
                next_first = next_group[0]

                # Insert blended frames between two groups
                for f in range(1, blend_frames + 1):
                    alpha = f / (blend_frames + 1)
                    blended_frame = (current_last * (1 - alpha) + next_first * alpha).astype(np.uint8)
                    smoothed_frames.append(blended_frame)

        return smoothed_frames

    def apply_group_pause_smoothing(self, frame_groups, pause_frames):
        """Apply pause smoothing to gloss groups"""
        smoothed_frames = []

        for i, group in enumerate(frame_groups):
            smoothed_frames.extend(group)

            # Add pause frames after each group (repeat last frame)
            if i < len(frame_groups) - 1:
                last_frame = group[-1]
                for _ in range(pause_frames):
                    smoothed_frames.append(last_frame.copy())

        return smoothed_frames

    def show_available_glosses(self, limit=20):
        """Show available glosses or video_ids"""
        if self.gloss_mapping:
            glosses = list(self.gloss_mapping.keys())
            print(f"\n📋 Available Glosses ({len(glosses)}):")
            for i, gloss in enumerate(glosses[:limit]):
                videos = self.gloss_mapping[gloss]
                if isinstance(videos, list):
                    print(f"  {gloss} -> {len(videos)} videos")
                else:
                    print(f"  {gloss} -> {videos}")
            if len(glosses) > limit:
                print(f"  ... and {len(glosses) - limit} more")
        else:
            video_ids = list(self.metadata['video_index'].keys())
            print(f"\n📋 Available Video IDs ({len(video_ids)}):")
            for i, vid in enumerate(video_ids[:limit]):
                frame_count = (self.metadata['video_index'][vid]['end_frame'] -
                               self.metadata['video_index'][vid]['start_frame'] + 1)
                print(f"  {vid} ({frame_count} frames)")
            if len(video_ids) > limit:
                print(f"  ... and {len(video_ids) - limit} more")

    def run_qa_system(self):
        """Run QA system"""
        print("\n" + "=" * 60)
        print("🤖 Sign Language Gloss Q&A System")
        print("=" * 60)
        print("💬 Enter gloss to convert, separate multiple words with spaces")
        print("📋 Enter 'list' to view available glosses/videos")
        print("🔧 Enter 'help' to view help")
        print("👋 Enter 'quit' to exit system")
        print("=" * 60)

        while True:
            try:
                user_input = input("\n🤖 Please enter gloss: ").strip()

                if not user_input:
                    continue
                elif user_input.lower() == 'quit':
                    print("👋 Thank you for using!")
                    break
                elif user_input.lower() == 'list':
                    self.show_available_glosses()
                    continue
                elif user_input.lower() == 'help':
                    self.show_help()
                    continue

                # Parse input gloss
                gloss_list = user_input.upper().split()
                print(f"\n🎯 Query: {' + '.join(gloss_list)}")

                # Get corresponding frames (select only one video per gloss)
                frame_indices, video_info = self.get_frames_for_glosses(gloss_list, one_video_per_gloss=True)

                if not frame_indices:
                    print("❌ No matching video frames found")
                    continue

                print(f"\n📊 Total found {len(frame_indices)} frames from {len(video_info)} videos")

                # If multiple videos, ask for smoothing options
                smoothing_method = 'none'
                smoothing_frames = 0

                if len(video_info) > 1:
                    print(f"\n🌊 Multiple video segments detected, choose smoothing transition method:")
                    print(f"   1. none - No smoothing (direct concatenation)")
                    print(f"   2. fade - Fade in/out transition")
                    print(f"   3. blend - Frame blending transition")
                    print(f"   4. pause - Add pause interval")

                    smooth_choice = input(f"Choose smoothing method [1-4, default 1]: ").strip()

                    if smooth_choice == '2':
                        smoothing_method = 'fade'
                        smoothing_frames = int(input("Fade in/out frames [default 5]: ").strip() or "5")
                    elif smooth_choice == '3':
                        smoothing_method = 'blend'
                        smoothing_frames = int(input("Blend frames [default 3]: ").strip() or "3")
                    elif smooth_choice == '4':
                        smoothing_method = 'pause'
                        smoothing_frames = int(input("Pause frames [default 10]: ").strip() or "10")

                # Generate output filename
                gloss_str = "_".join(gloss_list)
                timestamp = __import__('datetime').datetime.now().strftime("%Y%m%d_%H%M%S")
                suffix = f"_{smoothing_method}" if smoothing_method != 'none' else ""
                output_file = Path(OUTPUT_DIR) / f"{gloss_str}_{timestamp}{suffix}.mp4"

                # Ask user whether to generate video
                confirm = input(f"\n❓ Generate video to {output_file}? [y/n]: ").strip().lower()

                if confirm in ['y', 'yes', '']:
                    success = self.generate_video(
                        frame_indices, output_file, video_info,
                        smoothing_frames=smoothing_frames,
                        smoothing_method=smoothing_method
                    )

                    if success:
                        print(f"\n🎉 Video generated: {output_file}")

                        # Show video details
                        print(f"\n📈 Video details:")
                        for info in video_info:
                            print(f"   {info['gloss']}: {info['video_id']} ({info['frame_count']} frames)")
                else:
                    print("⏭️  Skipping video generation")

            except KeyboardInterrupt:
                print("\n\n👋 System exited")
                break
            except Exception as e:
                print(f"❌ Error occurred: {e}")

    def show_help(self):
        """Show help information"""
        print("\n" + "=" * 50)
        print("📖 Help Information")
        print("=" * 50)
        print("🔹 Enter single gloss: HELLO")
        print("🔹 Enter multiple glosses: HELLO WORLD GOODBYE")
        print("🔹 View available content: list")
        print("🔹 System will automatically match corresponding sign language videos")
        print(f"🔹 Generated videos are saved in {OUTPUT_DIR}/ directory")
        print("🔹 Supported mapping file format (gloss_mapping.json):")
        print('   {"HELLO": ["video1", "video2"], "WORLD": "video3"}')
        print("🔹 Smoothing transition options:")
        print("   - fade: Fade in/out transition")
        print("   - blend: Frame blending transition")
        print("   - pause: Add pause interval")
        print("=" * 50)


def main():
    parser = argparse.ArgumentParser(description='Sign Language Gloss Q&A System')
    parser.add_argument('--gloss', '-g',
                        help='Directly input gloss to generate video, separated by spaces')
    parser.add_argument('--fps', type=int, default=30,
                        help='Video frame rate (default: 30)')
    parser.add_argument('--width', type=int, default=480,
                        help='Video width (default: 480)')
    parser.add_argument('--height', type=int, default=480,
                        help='Video height (default: 480)')
    parser.add_argument('--smoothing', choices=['none', 'fade', 'blend', 'pause'],
                        default='none', help='Smoothing transition method (default: none)')
    parser.add_argument('--smoothing-frames', type=int, default=5,
                        help='Smoothing transition frames (default: 5)')

    args = parser.parse_args()

    # Initialize QA system
    qa_system = SignLanguageQA()

    # If gloss parameter is provided, process directly
    if args.gloss:
        gloss_list = args.gloss.upper().split()
        print(f"🎯 Processing gloss: {' + '.join(gloss_list)}")

        frame_indices, video_info = qa_system.get_frames_for_glosses(gloss_list, one_video_per_gloss=True)

        if frame_indices:
            gloss_str = "_".join(gloss_list)
            timestamp = __import__('datetime').datetime.now().strftime("%Y%m%d_%H%M%S")
            suffix = f"_{args.smoothing}" if args.smoothing != 'none' else ""
            output_file = Path(OUTPUT_DIR) / f"{gloss_str}_{timestamp}{suffix}.mp4"

            print(f"📊 Found {len(frame_indices)} frames from {len(video_info)} videos")
            if args.smoothing != 'none':
                print(f"🌊 Using {args.smoothing} smoothing transition ({args.smoothing_frames} frames)")

            success = qa_system.generate_video(
                frame_indices, output_file, video_info, args.fps, args.width, args.height,
                args.smoothing_frames, args.smoothing
            )

            if success:
                print(f"🎉 Video generated: {output_file}")
                print(f"\n📈 Video details:")
                for info in video_info:
                    print(f"   {info['gloss']}: {info['video_id']} ({info['frame_count']} 帧)")
        else:
            print("❌ No matching videos found")
    else:
        # Start interactive QA system
        qa_system.run_qa_system()


if __name__ == "__main__":
    main()