Add AllInOnePlayer

README.md

@@ -1,8 +1,14 @@
 # ComfyUI Video Player
 1 step closer to replacing all software with comfy
 ![preview](https://github.com/BetaDoggo/ComfyUI-VideoPlayer/blob/main/ComfyApple.gif)
-# Usage 
+
 Install this node as well as [ComfyUI-Custom-Scripts](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
+# Usage (automatic)
+1. Load allinoneworkflow.json
+2. Enter the full video path
+3. Check "Extra options" -> "Auto Queue"
+4. Click "Queue Prompt"
+# Usage (manual)
 1. Convert your file using the included convert-video.py or convert-video-color.py/convert-video-color-cuda.py (requires cuda-requirements.txt)
 2. Load the example workflow
 3. Set the framerate of the video

allinoneworkflow.json

@@ -0,0 +1,157 @@
+{
+  "last_node_id": 16,
+  "last_link_id": 11,
+  "nodes": [
+    {
+      "id": 7,
+      "type": "ShowText|pysssss",
+      "pos": [
+        1214,
+        338
+      ],
+      "size": {
+        "0": 1404.90625,
+        "1": 1109.595703125
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": 10,
+          "widget": {
+            "name": "text"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": null,
+          "shape": 6
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ShowText|pysssss"
+      },
+      "widgets_values": [
+        "",
+        "Failed to load frame. Either the video is over, the video path is wrong or there's another error. \nMake sure that you entered a direct path and that there are no \"s in the path."
+      ]
+    },
+    {
+      "id": 15,
+      "type": "AllInOnePlayer",
+      "pos": [
+        882,
+        341
+      ],
+      "size": [
+        315,
+        130
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "frame",
+          "type": "INT",
+          "link": 11,
+          "widget": {
+            "name": "frame"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": [
+            10
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "AllInOnePlayer"
+      },
+      "widgets_values": [
+        1,
+        "",
+        100,
+        30
+      ]
+    },
+    {
+      "id": 16,
+      "type": "PrimitiveNode",
+      "pos": [
+        883,
+        515
+      ],
+      "size": [
+        267.27526413341457,
+        82
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": [
+            11
+          ],
+          "slot_index": 0,
+          "widget": {
+            "name": "frame"
+          }
+        }
+      ],
+      "title": "Frame Counter\n",
+      "properties": {
+        "Run widget replace on values": false
+      },
+      "widgets_values": [
+        1,
+        "increment"
+      ]
+    }
+  ],
+  "links": [
+    [
+      10,
+      15,
+      0,
+      7,
+      0,
+      "STRING"
+    ],
+    [
+      11,
+      16,
+      0,
+      15,
+      0,
+      "INT"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.7513148009015777,
+      "offset": [
+        -552.0969407948444,
+        -147.57064944942996
+      ]
+    }
+  },
+  "version": 0.4
+}

nodes.py

@@ -2,8 +2,10 @@
 import cv2
 import time
 import torch
+import shutil
 import numpy as np
 from PIL import Image
+from comfy.utils import ProgressBar
 
 class LoadFrame:
     @classmethod
@@ -21,6 +23,7 @@ def INPUT_TYPES(s):
     CATEGORY = "VideoPlayer"
     def Loadframe(self, frame, frameRate, path):
         try:
+            path = path.replace('"', '') #make "copy as path" faster
             with open((path + str(frame) + ".txt"), 'r', encoding='utf-8') as file:
                 content = file.read()
                 timestamp = 0.00
@@ -45,8 +48,10 @@ def INPUT_TYPES(s):
     RETURN_TYPES = ("IMAGE", "FLOAT",)
     FUNCTION = "load_jpg_frame"
     CATEGORY = "VideoPlayer"
+
     def load_jpg_frame(self, frame, frameRate, path):
         try:
+            path = path.replace('"', '') #make "copy as path" faster
             image_path = os.path.join(path, f"{frame:05d}.jpg")
             with Image.open(image_path) as img:
                 img = img.convert("RGB")
@@ -75,8 +80,10 @@ def INPUT_TYPES(s):
     RETURN_TYPES = ("IMAGE", "FLOAT",)
     FUNCTION = "LoadVideoFrame"
     CATEGORY = "VideoPlayer"
+
     def LoadVideoFrame(self, video_path, frame, frameRate):
         try:
+            video_path = video_path.replace('"', '') #make "copy as path" faster
             cap = cv2.VideoCapture(video_path)
             cap.set(cv2.CAP_PROP_POS_FRAMES, frame - 1)  # Subtract 1 because frame count starts at 0
             ret, img = cap.read()
@@ -123,17 +130,111 @@ def ImageToEmoji(self, image, width):
         emoji_array = np.where(pixels > threshold, "⬜", "⬛")
         ascii_image = '\n'.join([''.join(row) for row in emoji_array])
         return(ascii_image,)
+
+class AllInOnePlayer:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "frame": ("INT", {"default": 1, "min": 1, "max": 100000, "step": 1, "forceInput": True}),
+                "video_path": ("STRING", {"forceInput": False}),
+                "width": ("INT", {"default": 100, "min": 10, "max": 200, "step": 1}),
+                "framerate": ("INT", {"default": 30, "min": 0, "max": 500, "step": 1}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "PlayVideo"
+    CATEGORY = "VideoPlayer"
+
+    def __init__(self):
+        self.node_dir = os.path.dirname(os.path.abspath(__file__))
+
+    def ImageToEmoji(self, image, width):
+        if len(image.shape) == 3:
+            image = np.mean(image, axis=2).astype(np.uint8)
+        else:
+            image = image.astype(np.uint8)
+        img = Image.fromarray(image)
+        pixels = np.array(img)
+        threshold = np.mean(pixels)
+        emoji_array = np.where(pixels > threshold, "⬜", "⬛")
+        ascii_image = '\n'.join([''.join(row) for row in emoji_array])
+        return ascii_image
+
+    def get_video_prefix(self, video_path):
+        return os.path.splitext(os.path.basename(video_path))[0]
+
+    def resize_frame(self, frame, target_width):
+        height, width = frame.shape[:2]
+        aspect_ratio = height / width
+        new_height = int(target_width * aspect_ratio)
+        return cv2.resize(frame, (target_width, new_height), interpolation=cv2.INTER_AREA)
+
+    def ExtractFrames(self, video_path, target_width):
+        temp_frames_dir = os.path.join(self.node_dir, "temp_frames")
+        shutil.rmtree(temp_frames_dir, ignore_errors=True)
+        os.makedirs(temp_frames_dir)
+        video_prefix = self.get_video_prefix(video_path)
+        cap = cv2.VideoCapture(video_path)
+        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+        #Initialize progress bar
+        progress = ProgressBar(10)
+        frame_count = 0
+        next_progress_update = total_frames // 10  # Calculate frames per 10%
+
+        while True:
+            ret, frame = cap.read()
+            if not ret:
+                break
+            resized_frame = self.resize_frame(frame, target_width)
+            emoji_frame = self.ImageToEmoji(resized_frame, target_width)
+
+            frame_filename = os.path.join(temp_frames_dir, f"{video_prefix}_frame_{frame_count:04d}.txt")
+            with open(frame_filename, 'w', encoding='utf-8') as f:
+                f.write(emoji_frame)
+
+            frame_count += 1
+            #Update progress bar every 10% of frames processed
+            if frame_count >= next_progress_update:
+                progress.update(1)
+                next_progress_update += total_frames // 10
+
+        cap.release()
+
+    def PlayVideo(self, frame, video_path, width, framerate):
+        video_path = video_path.replace('"', '') #make "copy as path" faster
+        progress = ProgressBar(10)
+        progress.update
+        temp_frames_dir = os.path.join(self.node_dir, "temp_frames")
+        video_prefix = self.get_video_prefix(video_path)
+
+        if not os.path.exists(temp_frames_dir) or not any(f.startswith(video_prefix) for f in os.listdir(temp_frames_dir)):
+            self.ExtractFrames(video_path, width)
+
+        frame_path = os.path.join(temp_frames_dir, f"{video_prefix}_frame_{frame:04d}.txt")
+        if os.path.exists(frame_path):
+            with open(frame_path, 'r', encoding='utf-8') as f:
+                emoji_frame = f.read()
+
+            if framerate != 0:
+                time.sleep(1/framerate)
+            return (emoji_frame,)
+        else:
+            return ("Failed to load frame. Either the video is over, the video path is wrong, or there's another error.",)
 
 NODE_CLASS_MAPPINGS = {
     "LoadFrame": LoadFrame,
     "LoadJPGFrame": LoadJPGFrame,
     "LoadVideoFrame": LoadVideoFrame,
-    "ImageToEmoji": ImageToEmoji
+    "ImageToEmoji": ImageToEmoji,
+    "AllInOnePlayer": AllInOnePlayer,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
     "LoadFrame": "LoadFrame",
     "LoadJPGFrame": "LoadJPGFrame",
     "LoadVideoFrame": "Load Video Frame",
-    "ImageToEmoji": "Image To Emoji"
+    "ImageToEmoji": "Image To Emoji",
+    "AllInOnePlayer": "AllInOnePlayer",
 }

requirements.txt

@@ -0,0 +1 @@
+opencv-python