import gradio as gr
import cv2
from PIL import Image
import numpy as np
from transformers import pipeline
import os
import torch
import torch.nn.functional as F
from torchvision import transforms
from torchvision.transforms import Compose
import trimesh
from geometry import create_triangles
import tempfile
from functools import partial
import spaces
from zipfile import ZipFile
import json

from depth_anything.dpt import DepthAnything
from depth_anything.util.transform import Resize, NormalizeImage, PrepareForNet
from moviepy.editor import *

edge = []
gradient = None
params = { "fnum":0, "l":16, "c":3 }
frame_selected = 0
frames = []
depths = []
masks = []
locations = []
mesh = []

def zip_files(files_in, files_out):
    with ZipFile("depth_result.zip", "w") as zipObj:
        for idx, file in enumerate(files_in):
            zipObj.write(file, file.split("/")[-1])
        for idx, file in enumerate(files_out):
            zipObj.write(file, file.split("/")[-1])
    return "depth_result.zip"

def create_video(frames, fps, type):
    print("building video result")
    clip = ImageSequenceClip(frames, fps=fps)
    clip.write_videofile(type + "_result.mp4", fps=fps)
    
    return type + "_result.mp4"

@torch.no_grad()
def predict_depth(model, image):
    return model(image)["depth"]

#@spaces.GPU
def make_video(video_path, outdir='./vis_video_depth', encoder='vits'):
    if encoder not in ["vitl","vitb","vits"]:
        encoder = "vits"

    mapper = {"vits":"small","vitb":"base","vitl":"large"}
    # DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
    # model = DepthAnything.from_pretrained('LiheYoung/depth_anything_vitl14').to(DEVICE).eval()
    # Define path for temporary processed frames
    temp_frame_dir = tempfile.mkdtemp()
    
    margin_width = 50
    to_tensor_transform = transforms.ToTensor()

    DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
    # depth_anything = DepthAnything.from_pretrained('LiheYoung/depth_anything_{}14'.format(encoder)).to(DEVICE).eval()
    depth_anything = pipeline(task = "depth-estimation", model=f"nielsr/depth-anything-{mapper[encoder]}")
    
    # total_params = sum(param.numel() for param in depth_anything.parameters())
    # print('Total parameters: {:.2f}M'.format(total_params / 1e6))
    
    transform = Compose([
        Resize(
            width=518,
            height=518,
            resize_target=False,
            keep_aspect_ratio=True,
            ensure_multiple_of=14,
            resize_method='lower_bound',
            image_interpolation_method=cv2.INTER_CUBIC,
        ),
        NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
        PrepareForNet(),
    ])

    if os.path.isfile(video_path):
        if video_path.endswith('txt'):
            with open(video_path, 'r') as f:
                lines = f.read().splitlines()
        else:
            filenames = [video_path]
    else:
        filenames = os.listdir(video_path)
        filenames = [os.path.join(video_path, filename) for filename in filenames if not filename.startswith('.')]
        filenames.sort()
    
    # os.makedirs(outdir, exist_ok=True)
    
    for k, filename in enumerate(filenames):
        file_size = os.path.getsize(filename)/1024/1024
        if file_size > 128.0:
            print(f'File size of {filename} larger than 128Mb, sorry!')
            return filename
        print('Progress {:}/{:},'.format(k+1, len(filenames)), 'Processing', filename)
        
        raw_video = cv2.VideoCapture(filename)
        frame_width, frame_height = int(raw_video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(raw_video.get(cv2.CAP_PROP_FRAME_HEIGHT))
        frame_rate = int(raw_video.get(cv2.CAP_PROP_FPS))
        if frame_rate < 1:
            frame_rate = 1
        cframes = int(raw_video.get(cv2.CAP_PROP_FRAME_COUNT))
        print(f'frames: {cframes}, fps: {frame_rate}')
        # output_width = frame_width * 2 + margin_width
        
        #filename = os.path.basename(filename)
        # output_path = os.path.join(outdir, filename[:filename.rfind('.')] + '_video_depth.mp4')
        #with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as tmpfile:
        #    output_path = tmpfile.name
        #out = cv2.VideoWriter(output_path, cv2.VideoWriter_fourcc(*"avc1"), frame_rate, (output_width, frame_height))
        #fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        #out = cv2.VideoWriter(output_path, fourcc, frame_rate, (output_width, frame_height))
        global masks
        count=0
        depth_frames = []
        orig_frames = []
        while raw_video.isOpened():
            ret, raw_frame = raw_video.read()
            if not ret:
                break

            frame = cv2.cvtColor(raw_frame, cv2.COLOR_BGR2RGB) / 255.0
            frame_pil =  Image.fromarray((frame * 255).astype(np.uint8))
            frame = transform({'image': frame})['image']
            
            frame = torch.from_numpy(frame).unsqueeze(0).to(DEVICE)
            
            
            depth = to_tensor_transform(predict_depth(depth_anything, frame_pil))

            depth = F.interpolate(depth[None], (frame_height, frame_width), mode='bilinear', align_corners=False)[0, 0]
            depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0
            
            depth = depth.cpu().numpy().astype(np.uint8)
            depth_color = cv2.applyColorMap(depth, cv2.COLORMAP_BONE)
            depth_gray = cv2.cvtColor(depth_color, cv2.COLOR_RGBA2GRAY)
            depth_color = cv2.cvtColor(depth_gray, cv2.COLOR_GRAY2BGR)

            # Remove white border around map:
            # define lower and upper limits of white
            white_lo = np.array([250,250,250])
            white_hi = np.array([255,255,255])
            # mask image to only select white
            mask = cv2.inRange(depth_color, white_lo, white_hi)
            # change image to black where we found white
            depth_color[mask>0] = (0,0,0)
            
            # split_region = np.ones((frame_height, margin_width, 3), dtype=np.uint8) * 255
            # combined_frame = cv2.hconcat([raw_frame, split_region, depth_color])
            
            # out.write(combined_frame)
            # frame_path = os.path.join(temp_frame_dir, f"frame_{count:05d}.png")
            # cv2.imwrite(frame_path, combined_frame)

            cv2.imwrite(f"f{count}.png", raw_frame)
            orig_frames.append(f"f{count}.png")
            
            cv2.imwrite(f"f{count}_dmap.png", depth_color)
            depth_frames.append(f"f{count}_dmap.png")
            masks.append(f"f{count}_dmap.png")
            count += 1

        final_vid = create_video(depth_frames, frame_rate, "depth")
        final_zip = zip_files(orig_frames, depth_frames)
        raw_video.release()
        # out.release()
        cv2.destroyAllWindows()

        global gradient
        global frame_selected
        global depths
        global frames
        frames = orig_frames
        depths = depth_frames

        if depth_color.shape[0] == 2048: #height
            masks[len(masks)-1] = './gradient_large.png'
            depth_frames[len(masks)-1] = './gradient_large.png'
            gradient = cv2.imread('./gradient_large.png').astype(np.uint8)
        elif depth_color.shape[0] == 1024:
            masks[len(masks)-1] = './gradient.png'
            depth_frames[len(masks)-1] = './gradient.png'
            gradient = cv2.imread('./gradient.png').astype(np.uint8)
        else:
            masks[len(masks)-1] = './gradient_small.png'
            depth_frames[len(masks)-1] = './gradient_small.png'
            gradient = cv2.imread('./gradient_small.png').astype(np.uint8)
        
        return final_vid, final_zip, frames, masks[frame_selected] #output_path

def depth_edges_mask(depth):
    """Returns a mask of edges in the depth map.
    Args:
    depth: 2D numpy array of shape (H, W) with dtype float32.
    Returns:
    mask: 2D numpy array of shape (H, W) with dtype bool.
    """
    # Compute the x and y gradients of the depth map.
    depth_dx, depth_dy = np.gradient(depth)
    # Compute the gradient magnitude.
    depth_grad = np.sqrt(depth_dx ** 2 + depth_dy ** 2)
    # Compute the edge mask.
    mask = depth_grad > 0.05
    return mask

def pano_depth_to_world_points(depth):
    """
    360 depth to world points
    given 2D depth is an equirectangular projection of a spherical image
    Treat depth as radius
    longitude : -pi to pi
    latitude : -pi/2 to pi/2
    """

    mask = cv2.inRange(depth, 225, 255)
    depth[mask>0] = 224

    # Convert depth to radius
    radius = (255 - depth.flatten())

    lon = np.linspace(0, np.pi*2, depth.shape[1])
    lat = np.linspace(0, np.pi, depth.shape[0])
    lon, lat = np.meshgrid(lon, lat)
    lon = lon.flatten()
    lat = lat.flatten()

    pts3d = [[0,0,0]]
    uv = [[0,0]]
    for i in range(0, 1): #(0,2)
        for j in range(0, 1): #(0,2)
            #rnd_lon = (np.random.rand(depth.shape[0]*depth.shape[1]) - 0.5) / 8
            #rnd_lat = (np.random.rand(depth.shape[0]*depth.shape[1]) - 0.5) / 8
            d_lon = lon + i/2 * np.pi*2 / depth.shape[1]
            d_lat = lat + j/2 * np.pi / depth.shape[0]
            
            # Convert to cartesian coordinates
            x = radius * np.cos(d_lon) * np.sin(d_lat)
            y = radius * np.cos(d_lat)
            z = radius * np.sin(d_lon) * np.sin(d_lat)
            
            pts = np.stack([x, y, z], axis=1)
            uvs = np.stack([lon, lat], axis=1)
            
            pts3d = np.concatenate((pts3d, pts), axis=0)
            uv = np.concatenate((uv, uvs), axis=0)
            #print(f'i: {i}, j: {j}')
            j = j+1
        i = i+1
        
    return [pts3d, uv]

def rgb2gray(rgb):
    return np.dot(rgb[...,:3], [0.333, 0.333, 0.333])

def get_mesh(image, depth, blur_data, loadall):
    global locations
    global mesh
    if loadall == False:
        mesh = []
    fnum = frame_selected

    #print(image[fnum][0])
    #print(depth["composite"])

    depthc = cv2.cvtColor(depth["background"], cv2.COLOR_RGBA2RGB)
    blur_img = blur_image(image[fnum][0], depthc, blur_data)
    gdepth = rgb2gray(depthc)
    
    print('depth to gray - ok')
    points = pano_depth_to_world_points(gdepth)
    pts3d = points[0]
    uv = points[1]
    print('radius from depth - ok')

    # Create a trimesh mesh from the points
    # Each pixel is connected to its 4 neighbors
    # colors are the RGB values of the image

    verts = pts3d.reshape(-1, 3)
    #triangles = create_triangles(image.shape[0], image.shape[1])
    #print('triangles - ok')
    rgba = cv2.cvtColor(blur_img, cv2.COLOR_RGB2RGBA)
    colors = rgba.reshape(-1, 4)
    clrs = [[128, 128, 128, 0]]

    for i in range(0,1): #(0,4)
        clrs = np.concatenate((clrs, colors), axis=0)
        i = i+1

    #mesh = trimesh.Trimesh(vertices=verts, faces=triangles, vertex_colors=colors)
    mesh.append(trimesh.PointCloud(verts, colors=clrs))
    #material = trimesh.visual.texture.SimpleMaterial(image=image)
    #texture = trimesh.visual.TextureVisuals(uv=uv, image=image, material=material)
    #mesh.visual = texture
        
    scene = trimesh.Scene(mesh)
    print('mesh - ok')

    # Save as glb
    glb_file = tempfile.NamedTemporaryFile(suffix='.glb', delete=False)
    glb_path = glb_file.name
    scene.export(glb_path)
    print('file - ok')
    return glb_path

def blur_image(image, depth, blur_data):
    blur_a = blur_data.split()
    print(f'blur data {blur_data}')

    blur_frame = image.copy()
    j = 0
    while j < 256:
        i = 255 - j
        blur_lo = np.array([i,i,i])
        blur_hi = np.array([i+1,i+1,i+1])
        blur_mask = cv2.inRange(depth, blur_lo, blur_hi)
        
        print(f'kernel size {int(blur_a[j])}')
        blur = cv2.GaussianBlur(image, (int(blur_a[j]), int(blur_a[j])), 0)
                
        blur_frame[blur_mask>0] = blur[blur_mask>0]
        j = j + 1

    return blur_frame

def loadurl(url):
    return url


def select_frame(v, evt: gr.SelectData):
    global frame_selected
    global masks
    global edge
    
    if evt.index != frame_selected:
        masks[frame_selected] = v
        frame_selected = evt.index
        edge = []
        
    return masks[frame_selected], frame_selected

def switch_rows(v):
    global frames
    global depths
    if v == True:
        print(depths[0])
        return depths
    else:
        print(frames[0])
        return frames

def apply_mask(d):
    global frame_selected
    global masks
    
    masks[frame_selected] = d["background"]
    cv2.imwrite(f"f{frame_selected}_dmap.png", masks[frame_selected])
    return masks[frame_selected], f"f{frame_selected}_dmap.png"

def draw_mask(l, c, t, v, d, evt: gr.EventData):
    global params
    global frame_selected
    global masks
    global gradient
    global edge
    
    points = json.loads(v)
    pts = np.array(points, np.int32)
    pts = pts.reshape((-1,1,2))

    x = points[len(points)-1][0]
    y = points[len(points)-1][1]

    scale = 1
    delta = 0
    ddepth = cv2.CV_16S

    if len(edge) == 0 or params["fnum"] != frame_selected or params["l"] != l or params["c"] != c:
      if len(edge) > 0:
          d["background"] = cv2.imread(masks[frame_selected]).astype(np.uint8)

      bg = cv2.cvtColor(d["background"], cv2.COLOR_RGBA2GRAY)

      diff = (bg-cv2.cvtColor(gradient, cv2.COLOR_RGBA2GRAY)).astype(np.uint8)
      mask = cv2.inRange(diff, -int(c/2), int(c/2))
      #kernel = np.ones((c,c),np.float32)/(c*c)
      #mask = cv2.filter2D(mask,-1,kernel)
      grad_x = cv2.convertScaleAbs(cv2.Sobel(mask, ddepth, 1, 0, ksize=1, scale=scale, delta=delta, borderType=cv2.BORDER_DEFAULT))
      grad_y = cv2.convertScaleAbs(cv2.Sobel(mask, ddepth, 0, 1, ksize=1, scale=scale, delta=delta, borderType=cv2.BORDER_DEFAULT))
      grad = cv2.convertScaleAbs(cv2.Sobel(mask, ddepth, 1, 1, ksize=1, scale=scale, delta=delta, borderType=cv2.BORDER_DEFAULT))
    
      grad_y = cv2.addWeighted(grad_x, 0.5, grad_y, 0.5, 0)
      grad = cv2.addWeighted(grad_y, 0.5, grad, 0.5, 0)

      mask = mask + cv2.inRange(grad, 1, 255)

      indices = np.arange(0,256)   # List of all colors 
      divider = np.linspace(0,255,l+1)[1] # we get a divider
      quantiz = np.int0(np.linspace(0,255,l)) # we get quantization colors
      color_levels = np.clip(np.int0(indices/divider),0,l-1) # color levels 0,1,2..
      palette = quantiz[color_levels]

      #for i in range(l):
      #    bg[(bg >= i*255/l) & (bg < (i+1)*255/l)] = i*255/(l-1)
      bg = cv2.convertScaleAbs(palette[bg]).astype(np.uint8) # Converting image back to uint
      bg[mask>0] = 255

      params["fnum"] = frame_selected
      params["l"] = l
      params["c"] = c

      #d["layers"][0] = cv2.cvtColor(bg, cv2.COLOR_GRAY2RGBA)
      edge = bg.copy()
    else:
      bg = edge.copy()
    
    mask = cv2.floodFill(bg, None, (x, y), 1, int(t*256/l), int(t*256/l))[2] #, (4 | cv2.FLOODFILL_FIXED_RANGE | cv2.FLOODFILL_MASK_ONLY | 255 << 8)
    # 255 << 8 tells to fill with the value 255)
    mask = mask[1:mask.shape[0]-1, 1:mask.shape[1]-1]
    
    d["layers"][0][mask>0] = (0,0,0,255)
    d["background"][mask>0] = (0,0,0,255)
    
    return gr.ImageEditor(value=d)


css = """
#img-display-container {
    max-height: 100vh;
    }
#img-display-input {
    max-height: 80vh;
    }
#img-display-output {
    max-height: 80vh;
    }
"""

title = "# Depth Anything Video Demo"
description = """Depth Anything on full video files.  
Please refer to our [paper](https://arxiv.org/abs/2401.10891), [project page](https://depth-anything.github.io), or [github](https://github.com/LiheYoung/Depth-Anything) for more details.  
Mesh rendering from [ZoeDepth](https://huggingface.co/spaces/shariqfarooq/ZoeDepth) ([github](https://github.com/isl-org/ZoeDepth/tree/main/ui))."""

transform = Compose([
        Resize(
            width=518,
            height=518,
            resize_target=False,
            keep_aspect_ratio=True,
            ensure_multiple_of=14,
            resize_method='lower_bound',
            image_interpolation_method=cv2.INTER_CUBIC,
        ),
        NormalizeImage(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
        PrepareForNet(),
])

# @torch.no_grad()
# def predict_depth(model, image):
#     return model(image)

with gr.Blocks(css=css) as demo:
    gr.Markdown(title)
    gr.Markdown(description)
    gr.Markdown("### Video Depth Prediction demo")

    with gr.Row():
        with gr.Column():
            input_url = gr.Textbox(value="./examples/streetview.mp4", label="URL")
            input_video = gr.Video(label="Input Video", format="mp4")
            input_url.change(fn=loadurl, inputs=[input_url], outputs=[input_video])
            output_frame = gr.Gallery(label="Frames", preview=True, columns=8192, type="numpy")
            output_switch = gr.Checkbox(label="Show depths")
            output_switch.input(fn=switch_rows, inputs=[output_switch], outputs=[output_frame])
            output_mask = gr.ImageEditor(layers=False, sources=('upload', 'clipboard'), show_download_button=True, type="numpy", interactive=True, transforms=(None,), eraser=gr.Eraser(), brush=gr.Brush(default_size=0, colors=['black', '#505050', '#a0a0a0', 'white']), elem_id="image_edit")
            depth_file = gr.File(label="Edited depth")
            output_mask.apply(fn=apply_mask, inputs=[output_mask], outputs=[output_mask, depth_file])
            with gr.Accordion(label="Edge", open=False):
              levels = gr.Slider(label="Color levels", value=16, maximum=32, minimum=2, step=1)
              contour = gr.Slider(label="Contour width", value=3, maximum=15, minimum=1, step=2)
              tolerance = gr.Slider(label="Flood fill tolerance", value=0, maximum=15, minimum=0, step=1)
              mouse = gr.Textbox(elem_id="mouse", value="""[]""", interactive=False)
              mouse.input(fn=draw_mask, show_progress="minimal", inputs=[levels, contour, tolerance, mouse, output_mask], outputs=[output_mask])
            selector = gr.HTML(value="""
            <a href='#' id='selector' onclick='this.style.fontWeight=\"bold\";
            document.getElementById(\"image_edit\").getElementsByTagName(\"canvas\")[0].oncontextmenu = function(e){e.preventDefault();}
            document.getElementById(\"image_edit\").getElementsByTagName(\"canvas\")[0].ondrag = function(e){e.preventDefault();}
            
            document.getElementById(\"image_edit\").getElementsByTagName(\"canvas\")[0].onclick = function(e) {
              var x = parseInt((e.clientX-e.target.getBoundingClientRect().x)*e.target.width/e.target.getBoundingClientRect().width);
              var y = parseInt((e.clientY-e.target.getBoundingClientRect().y)*e.target.height/e.target.getBoundingClientRect().height);

              var p = document.getElementById(\"mouse\").getElementsByTagName(\"textarea\")[0].value.slice(1, -1);
              if (p != \"\") { p += \", \"; }
              p += \"[\" + x + \", \" + y + \"]\";
              document.getElementById(\"mouse\").getElementsByTagName(\"textarea\")[0].value = \"[\" + p + \"]\";
              
              var evt = document.createEvent(\"Event\");
              evt.initEvent(\"input\", true, false);
              document.getElementById(\"mouse\").getElementsByTagName(\"textarea\")[0].dispatchEvent(evt);
            }
            document.getElementById(\"image_edit\").getElementsByTagName(\"canvas\")[0].onpointerdown = function(e) {
              
              document.getElementById(\"mouse\").getElementsByTagName(\"textarea\")[0].style.borderColor = \"#a0a0a0\";
            
            }
            document.getElementById(\"image_edit\").getElementsByTagName(\"canvas\")[0].onpointerup = function(e) {
              
              document.getElementById(\"mouse\").getElementsByTagName(\"textarea\")[0].style.borderColor = \"#ffffff\";
            
            }' title='Select point' style='text-decoration:none;color:white;'>⊹ Select point</a> <a href='#' id='clear_select' onclick='
              
              document.getElementById(\"mouse\").getElementsByTagName(\"textarea\")[0].value = \"[]\";
            
            ' title='Clear selection' style='text-decoration:none;color:white;'>✕ Clear selection</a>""")
            submit = gr.Button("Submit")
        with gr.Column():
            model_type = gr.Dropdown([("small", "vits"), ("base", "vitb"), ("large", "vitl")], type="value", value="vits", label='Model Type')
            processed_video = gr.Video(label="Output Video", format="mp4")
            processed_zip = gr.File(label="Output Archive")
            result = gr.Model3D(label="3D Mesh", clear_color=[0.5, 0.5, 0.5, 0.0], camera_position=[0, 90, 0], interactive=True, elem_id="model3D")   
            svg_in = gr.HTML(value="""<svg id='svg_in' height='32' width='256' viewBox='0 0 256 32' xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' style='touch-action:none;background-color:#808080;' onpointerdown='
              try{
                if (document.getElementById(\"pl\").getAttribute(\"points\").length < 256) {
                  var pts = \"\";
                  for (var i=0; i<256; i++) {
                    pts += i+\",0 \";
                  }
                  document.getElementById(\"pl\").setAttribute(\"points\", pts.slice(0,-1)); 
                  var xold = 0;
                  var yold = 0;
                  var x = 0;
                  var y = 0;
                  function lerp(y1, y2, mu) { return y1*(1-mu)+y2*mu; }
                  
                  this.onpointermove = function(event) {
                    if (this.title != \"\") {
                      x = parseInt(event.clientX - this.getBoundingClientRect().x);
                      y = parseInt(event.clientY - this.getBoundingClientRect().y);
                      if (x < 0) { x = 0; } else if (x > 255) { x = 255; }
                      if (y < 0) { y = 0; } else if (y > 31) { y = 31; }
                      var pl_a = document.getElementById(\"pl\").getAttribute(\"points\").split(\" \");
                      
                      for (var i=Math.min(xold, x)+1; i<Math.max(xold, x); i++) {
                        pl_a[i] = x+\",\"+parseInt(lerp( yold, y, (i-xold)/(x-xold) ));
                      }
                      pl_a[x] = x+\",\"+y;
                      xold = x;
                      yold = y;
                      document.getElementById(\"pl\").setAttribute(\"points\", pl_a.join(\" \"));
                    }
                  }
                  this.onpointerup = function(event) {
                    var pl_a = document.getElementById(\"pl\").getAttribute(\"points\").replace(/\d+,/g, \"\").split(\" \"); 
                    for (var i=0; i<pl_a.length; i++) {
                      pl_a[i] = parseInt(pl_a[i]) * 2 + 1;
                    }
                    document.getElementsByTagName(\"textarea\")[2].value = pl_a.join(\" \");
                    var evt = document.createEvent(\"Event\");
                    evt.initEvent(\"input\", true, false);
                    document.getElementsByTagName(\"textarea\")[2].dispatchEvent(evt);
                    this.title = \"\";
                  }
                  this.onpointerleave = function(event) {
                    this.title = \"\";
                  }
                  this.onpointerdown = function(event) {
                    xold = parseInt(event.clientX - this.getBoundingClientRect().x);
                    yold = parseInt(event.clientY - this.getBoundingClientRect().y);
                    this.title = xold+\",\"+yold;
                  }
                }
              }catch(e){alert(e);}
              '>
                <defs>
                  <linearGradient id='lg' x1='0%' x2='100%' y1='0%' y2='0%'>
                    <stop offset='0%' stop-color='white'/>
                    <stop offset='100%' stop-color='black'/>
                  </linearGradient>
                </defs>
                <polyline id='pl' points='-3,0 0,15 255,15 258,0' stroke='url(#lg)' fill='none' stroke-width='3' stroke-linejoin='round'/>
              </svg>""")
            average = gr.HTML(value="""<label for='average'>Average</label><input id='average' type='range' style='width:256px;height:1em;' value='1' min='1' max='15' step='2' onclick='
              var pts_a = document.getElementsByTagName(\"textarea\")[1].value.split(\" \");
              for (var i=0; i<256; i++) {
                var avg = 0;
                var div = this.value;
                for (var j = i-parseInt(this.value/2); j <= i+parseInt(this.value/2); j++) {
                  if (pts_a[j]) {
                    avg += parseInt(pts_a[j]);
                  } else {
                    div--;
                  }
                }
                pts_a[i] = parseInt((avg / div - 1) / 2) * 2 + 1;
              }
              document.getElementsByTagName(\"textarea\")[1].value = pts_a.join(\" \");
              for (var i=0; i<pts_a.length; i++) {
                pts_a[i] = i+\",\"+parseInt((pts_a[i] - 1) / 2);
              }
              document.getElementById(\"pl\").setAttribute(\"points\", pts_a.join(\" \"));

              var evt = document.createEvent(\"Event\");
              evt.initEvent(\"input\", true, false);
              document.getElementsByTagName(\"textarea\")[1].dispatchEvent(evt);
            ' oninput='
              this.parentNode.childNodes[2].innerText = this.value;
            '/><span>1</span>""")
            with gr.Accordion(label="Blur levels", open=False):
                blur_in = gr.Textbox(value="", label="Kernel size", show_label=False)
            with gr.Accordion(label="Locations", open=False):
                offset = gr.HTML(value="""<input type='text' id='kbrd' onkeydown='
                if (BABYLON) {
                  if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata) {
                    var evt = document.createEvent(\"Event\");
                    evt.initEvent(\"click\", true, false);
                    document.getElementById(\"reset_cam\").dispatchEvent(evt);
                  } 
                  event.preventDefault();
                  if (BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotationQuaternion) {
                    BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotationQuaternion = null;
                  }
                  switch(event.key) {
                    case \"w\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.y += 1;
                      this.value = \"w ⬆ x\";
                      break;
                    case \"x\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.y -= 1;
                      this.value = \"w ⬇ x\";
                      break;
                    case \"a\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.z -= 1;
                      this.value = \"a ⬅ d\";
                      break;
                    case \"d\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.z += 1;
                      this.value = \"a ➡ d\";
                      break;
                    case \"e\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.x -= 1;
                      this.value = \"z ↗ e\";
                      break;
                    case \"z\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.x += 1;
                      this.value = \"z ↙ e\";
                      break;
                    case \"s\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.x = 0;
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.y = 0;
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].position.z = 0;
                      this.value = \"\";
                      break;
                    case \"t\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.z += Math.PI/256;
                      this.value = \"t 🔃 b\";
                      break;
                    case \"b\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.z -= Math.PI/256;
                      this.value = \"t 🔃 b\";
                      break;
                    case \"f\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.y -= Math.PI/256;
                      this.value = \"f 🔁 h\";
                      break;
                    case \"h\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.y += Math.PI/256;
                      this.value = \"f 🔁 h\";
                      break;
                    case \"y\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.x -= Math.PI/256;
                      this.value = \"v 🔄 y\";
                      break;
                    case \"v\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.x += Math.PI/256;
                      this.value = \"v 🔄 y\";
                      break;
                    case \"g\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.x = 0;
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.y = 0;
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].rotation.z = 0;
                      this.value = \"\";
                      break;
                    case \"i\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.y *= 256/255;
                      this.value = \"i ↕ ,\";
                      break;
                    case \",\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.y /= 256/255;
                      this.value = \"i ↕ ,\";
                      break;
                    case \"j\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.z /= 256/255;
                      this.value = \"j ↔ l\";
                      break;
                    case \"l\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.z *= 256/255;
                      this.value = \"j ↔ l\";
                      break;
                    case \"o\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.x /= 256/255;
                      this.value = \"m ⤢ o\";
                      break;
                    case \"m\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.x *= 256/255;
                      this.value = \"m ⤢ o\";
                      break;
                    case \"k\":
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.x = 1;
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.y = 1;
                      BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].scaling.z = 1;
                      this.value = \"\";
                      break;
                    default:
                      this.value = \"\"; 
                  }
                }
                ' style='color:auto;background-color:transparent;border:1px solid lightgray;'/><pre id='keymap'>
`  1  2  3  4  5  6  7  8  9  0  -  =  
       W  E     T  Y     I  O     {  }
     A-`S´-D  F-`G´-H  J-`K´-L  ;  '
      Z´ X̀     V´ B̀     M´ `,  .  /
      <a id='move' href='#'>move</a>    <a id='rotate' href='#'>rotate</a>    <a id='scale' href='#'>scale</a>
                </pre>""")
                selected = gr.Number(elem_id="fnum", value=0, minimum=0, maximum=256, interactive=False)
                output_frame.select(fn=select_frame, inputs=[output_mask], outputs=[output_mask, selected])
                example_coords = """[
                  {"latLng": { "lat": 50.07379596793083, "lng": 14.437146122950555 } },
                  {"latLng": { "lat": 50.073799567020004, "lng": 14.437146774240507 } },
                  {"latLng": { "lat": 50.07377647505558, "lng": 14.437161000659017 } },
                  {"latLng": { "lat": 50.07379496839027, "lng": 14.437148958238538 } },
                  {"latLng": { "lat": 50.073823157821664, "lng": 14.437124189538856 } }
                ]"""
                coords = gr.JSON(elem_id="coords", value=example_coords, label="Precise coordinates", show_label=False)      
                
            html = gr.HTML(value="""<label for='zoom'>Zoom</label><input id='zoom' type='range' style='width:256px;height:1em;' value='0.8' min='0.157' max='1.57' step='0.001' oninput='
              if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata) {
                var evt = document.createEvent(\"Event\");
                evt.initEvent(\"click\", true, false);
                document.getElementById(\"reset_cam\").dispatchEvent(evt);
              } 
              BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].material.pointSize = Math.ceil(Math.log2(Math.PI/this.value));
              BABYLON.Engine.LastCreatedScene.activeCamera.fov = this.value;
              this.parentNode.childNodes[2].innerText = BABYLON.Engine.LastCreatedScene.activeCamera.fov;

              document.getElementById(\"model3D\").getElementsByTagName(\"canvas\")[0].style.filter = \"blur(\" + BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].material.pointSize/2.0*Math.sqrt(2.0) + \"px)\";
            '/><span>0.8</span>""")
            camera = gr.HTML(value="""<a href='#' id='reset_cam' onclick='
              if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata) {
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata = { 
                  screenshot: true,
                  pipeline: new BABYLON.DefaultRenderingPipeline(\"default\", true, BABYLON.Engine.LastCreatedScene, [BABYLON.Engine.LastCreatedScene.activeCamera]) 
                }
              } 
              BABYLON.Engine.LastCreatedScene.activeCamera.radius = 0;
              BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].material.pointSize = Math.ceil(Math.log2(Math.PI/document.getElementById(\"zoom\").value));
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.samples = 4; 
              BABYLON.Engine.LastCreatedScene.activeCamera.fov = document.getElementById(\"zoom\").value;
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.imageProcessing.contrast = document.getElementById(\"contrast\").value;
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.imageProcessing.exposure = document.getElementById(\"exposure\").value;
              
              document.getElementById(\"model3D\").getElementsByTagName(\"canvas\")[0].style.filter = \"blur(\" + BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1].material.pointSize/2.0*Math.sqrt(2.0) + \"px)\";
              document.getElementById(\"model3D\").getElementsByTagName(\"canvas\")[0].oncontextmenu = function(e){e.preventDefault();}
              document.getElementById(\"model3D\").getElementsByTagName(\"canvas\")[0].ondrag = function(e){e.preventDefault();}

              if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager) {
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager = new BABYLON.GizmoManager(BABYLON.Engine.LastCreatedScene, 16);
                
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.positionGizmoEnabled = true;
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.rotationGizmoEnabled = false;
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.scaleGizmoEnabled = false;
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.boundingBoxGizmoEnabled = false;
              
                BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.usePointerToAttachGizmos = false;
                document.getElementById(\"move\").onclick = function(event) {
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.positionGizmoEnabled = true;
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.rotationGizmoEnabled = false;
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.scaleGizmoEnabled = false;
                }
                document.getElementById(\"rotate\").onclick = function(event) {
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.positionGizmoEnabled = false;
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.rotationGizmoEnabled = true;
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.scaleGizmoEnabled = false;
                }
                document.getElementById(\"scale\").onclick = function(event) {
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.positionGizmoEnabled = false;
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.rotationGizmoEnabled = false;
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.scaleGizmoEnabled = true;
                }
              }
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.gizmoManager.attachToMesh(BABYLON.Engine.LastCreatedScene.getNodes()[parseInt(document.getElementById(\"fnum\").getElementsByTagName(\"input\")[0].value)+1]);

            '>reset camera</a>""")
            contrast = gr.HTML(value="""<label for='contrast'>Contrast</label><input id='contrast' type='range' style='width:256px;height:1em;' value='2.0' min='0' max='2' step='0.001' oninput='
              if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata) {
                var evt = document.createEvent(\"Event\");
                evt.initEvent(\"click\", true, false);
                document.getElementById(\"reset_cam\").dispatchEvent(evt);
              } 
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.imageProcessing.contrast = this.value;
              this.parentNode.childNodes[2].innerText = BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.imageProcessing.contrast;
            '/><span>2.0</span>""")
            exposure = gr.HTML(value="""<label for='exposure'>Exposure</label><input id='exposure' type='range' style='width:256px;height:1em;' value='0.5' min='0' max='2' step='0.001' oninput='
              if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata) {
                var evt = document.createEvent(\"Event\");
                evt.initEvent(\"click\", true, false);
                document.getElementById(\"reset_cam\").dispatchEvent(evt);
              } 
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.imageProcessing.exposure = this.value;
              this.parentNode.childNodes[2].innerText = BABYLON.Engine.LastCreatedScene.activeCamera.metadata.pipeline.imageProcessing.exposure;
            '/><span>0.5</span>""")
            canvas = gr.HTML(value="""<a href='#' onclick='
              if (!BABYLON.Engine.LastCreatedScene.activeCamera.metadata) {
                var evt = document.createEvent(\"Event\");
                evt.initEvent(\"click\", true, false);
                document.getElementById(\"reset_cam\").dispatchEvent(evt);
              } 
              BABYLON.Engine.LastCreatedScene.activeCamera.metadata.screenshot = true;

              BABYLON.Engine.LastCreatedScene.getEngine().onEndFrameObservable.add(function() {
                if (BABYLON.Engine.LastCreatedScene.activeCamera.metadata.screenshot === true) {
                  BABYLON.Engine.LastCreatedScene.activeCamera.metadata.screenshot = false;
                  try {
                    BABYLON.Tools.CreateScreenshotUsingRenderTarget(BABYLON.Engine.LastCreatedScene.getEngine(), BABYLON.Engine.LastCreatedScene.activeCamera, 
                      { precision: 1.0 }, (durl) => { 
                        var cnvs = document.getElementById(\"model3D\").getElementsByTagName(\"canvas\")[0]; //.getContext(\"webgl2\");
                        var svgd = `<svg id=\"svg_out\" viewBox=\"0 0 ` + cnvs.width + ` ` + cnvs.height + `\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">
                          <defs>
                            <filter id=\"blur\" x=\"0\" y=\"0\" xmlns=\"http://www.w3.org/2000/svg\">
                              <feGaussianBlur in=\"SourceGraphic\" stdDeviation=\"` + BABYLON.Engine.LastCreatedScene.getNodes()[1].material.pointSize/2.0*Math.sqrt(2.0) + `\" />
                            </filter>
                          </defs>
                          <image filter=\"url(#blur)\" id=\"svg_img\" x=\"0\" y=\"0\" width=\"` + cnvs.width + `\" height=\"` + cnvs.height + `\" xlink:href=\"` + durl + `\"/>
                        </svg>`;
                        document.getElementById(\"cnv_out\").width = cnvs.width;
                        document.getElementById(\"cnv_out\").height = cnvs.height;
                        document.getElementById(\"img_out\").src = \"data:image/svg+xml;base64,\" + btoa(svgd);        
                      }
                    );
                  } catch(e) { alert(e); }
                  // https://forum.babylonjs.com/t/best-way-to-save-to-jpeg-snapshots-of-scene/17663/11
                }
              });
            '/>snapshot</a><br/><img src='' id='img_out' onload='
              var ctxt = document.getElementById(\"cnv_out\").getContext(\"2d\");
              ctxt.drawImage(this, 0, 0); 
            '/><br/>
            <canvas id='cnv_out'/>""")
            load_all = gr.Checkbox(label="Load all")
            render = gr.Button("Render")
    
    def on_submit(uploaded_video,model_type,coordinates):
        global locations
        locations = []
        avg = [0, 0]
        
        if not coordinates:
            locations = json.loads(example_coords)
            for k, location in enumerate(locations):
                locations[k] = location["latLng"]
                avg[0] = avg[0] + locations[k]["lat"]
                avg[1] = avg[1] + locations[k]["lng"]
        else:
            locations = json.loads(coordinates)
            for k, location in enumerate(locations):
                locations[k] = location["location"]["latLng"]
                avg[0] = avg[0] + locations[k]["lat"]
                avg[1] = avg[1] + locations[k]["lng"]
                
        avg[0] = avg[0] / len(locations)
        avg[1] = avg[1] / len(locations)
        for k, location in enumerate(locations):
            locations[k]["lat"] = location["lat"] - avg[0]
            locations[k]["lng"] = location["lng"] - avg[1]
        print(locations)
            
        # Process the video and get the path of the output video
        output_video_path = make_video(uploaded_video,encoder=model_type)

        return output_video_path + (locations,)

    submit.click(on_submit, inputs=[input_video, model_type, coords], outputs=[processed_video, processed_zip, output_frame, output_mask, coords])
    render.click(partial(get_mesh), inputs=[output_frame, output_mask, blur_in, load_all], outputs=[result])

    example_files = os.listdir('examples')
    example_files.sort()
    example_files = [os.path.join('examples', filename) for filename in example_files]
    
    examples = gr.Examples(examples=example_files, inputs=[input_video], outputs=[processed_video, processed_zip, output_frame, output_mask, coords], fn=on_submit, cache_examples=True)
    

if __name__ == '__main__':
    demo.queue().launch()