import json
import os
from typing import Tuple, List, Union, Dict, Any
from util import Visualize
from PIL import Image, ImageDraw, ImageFont

#TODO input your work dir
BASE_DIR = ""

single_img_tasks_no_labels = ["Scene_Classification", "Orientation_Classification", "Environment_State_Classification", "Urban_OCR", "Class_Agnostic_Counting", "Referring_Expression_Counting", "Cross_Object_Reasoning"]

single_img_tasks_w_labels = ["Ground_Target_Planning"]

multi_img_tasks_no_labels = ["Target_Backtracking", "Intent_Analysis_and_Prediction", "Scene_Attribute_Understanding", "Scene_Damage_Assessment", "Scene_Analysis_and_Prediction", "Temporal_Ordering"]

multi_img_tasks_w_labels = ["Air_Ground_Collaborative_Planning", "Swarm_Collaborative_Planning"]

video_task = ["Event_Prediction", "Event_Tracing", "Event_Understanding"]

def process_multi_img_tasks_w_labels(task_list, BASE_DIR):
    for task in task_list:
        print(f"======Processing {task}======")
        qa = json.load(open(os.path.join(BASE_DIR, "tasks", f"{task}.json"), 'r', encoding='utf-8'))
        for d in qa:
            for item in d["metadata"]["data_resources"]:
                raw_img_p = os.path.join(BASE_DIR, item["path"].replace("annotated", "raw"))
                annotations = []
                for entity in d["target_entities"]:
                    if entity["index"] == item["index"]:
                        annotations.append(entity)
                vis_img = Visualize(
                    image=Image.open(raw_img_p),
                    annotations=annotations,
                    show_labels=True,
                )
                save_img_p = os.path.join(BASE_DIR, item["path"])
                os.makedirs(os.path.dirname(save_img_p), exist_ok=True)
                vis_img.save(save_img_p, quality=100, subsampling=0)
        print(f"======Processing End {task}======")    

def process_multi_img_tasks_no_labels(task_list, BASE_DIR):
    for task in task_list:
        print(f"======Processing {task}======")
        qa = json.load(open(os.path.join(BASE_DIR, "tasks", f"{task}.json"), 'r', encoding='utf-8'))
        for d in qa:
            for item in d["metadata"]["data_resources"]:
                raw_img_p = os.path.join(BASE_DIR, item["path"].replace("annotated", "raw"))
                annotations = []
                for entity in d["target_entities"]:
                    if entity["index"] == item["index"]:
                        annotations.append(entity)
                vis_img = Visualize(
                    image=Image.open(raw_img_p),
                    annotations=annotations,
                    show_labels=False,
                )
                save_img_p = os.path.join(BASE_DIR, item["path"])
                os.makedirs(os.path.dirname(save_img_p), exist_ok=True)
                vis_img.save(save_img_p, quality=100, subsampling=0)
        print(f"======Processing End {task}======")

def process_single_img_tasks_no_labels(task_list, BASE_DIR):
    for task in task_list:
        print(f"======Processing {task}======")
        qa = json.load(open(os.path.join(BASE_DIR, "tasks", f"{task}.json"), 'r', encoding='utf-8'))
        for d in qa:
            assert (d["metadata"]["data_type"] == "single_image") and (len(d["metadata"]["data_resources"]) == 1)
            raw_img_p = os.path.join(BASE_DIR, d["metadata"]["data_resources"][0]["path"].replace("annotated", "raw"))
            vis_img = Visualize(
                image=Image.open(raw_img_p),
                annotations=d["target_entities"],
                show_labels=False,
            )
            save_img_p = os.path.join(BASE_DIR, d["metadata"]["data_resources"][0]["path"])
            os.makedirs(os.path.dirname(save_img_p), exist_ok=True)
            vis_img.save(save_img_p, quality=100, subsampling=0)
        print(f"======Processing End {task}======")

def process_single_img_tasks_w_labels(task_list, BASE_DIR):
    for task in task_list:
        print(f"======Processing Start {task}======")
        qa = json.load(open(os.path.join(BASE_DIR, "tasks", f"{task}.json"), 'r', encoding='utf-8'))
        for d in qa:
            assert (d["metadata"]["data_type"] == "single_image") and (len(d["metadata"]["data_resources"]) == 1)
            raw_img_p = os.path.join(BASE_DIR, d["metadata"]["data_resources"][0]["path"].replace("annotated", "raw"))
            vis_img = Visualize(
                image=Image.open(raw_img_p),
                annotations=d["target_entities"],
                show_labels=True,
            )
            save_img_p = os.path.join(BASE_DIR, d["metadata"]["data_resources"][0]["path"])
            os.makedirs(os.path.dirname(save_img_p), exist_ok=True)
            vis_img.save(save_img_p, quality=100, subsampling=0)
        print(f"======Processing End {task}======")

if __name__ == "__main__":
    process_single_img_tasks_no_labels(single_img_tasks_no_labels, BASE_DIR)
    process_single_img_tasks_w_labels(single_img_tasks_w_labels, BASE_DIR) 
    process_multi_img_tasks_no_labels(multi_img_tasks_no_labels, BASE_DIR)
    process_multi_img_tasks_w_labels(multi_img_tasks_w_labels, BASE_DIR)