update

app.py

@@ -1,99 +1,33 @@
+import cv2
 import gradio as gr
 import os
-import time
-import json
-import yaml
-import pandas as pd
-from datetime import datetime
-from moviepy.editor import VideoFileClip
 
-# Function to process the video
-def process_video(video):
-    start_time = time.time()
+def convert_to_grayscale(video_file):
+    cap = cv2.VideoCapture(video_file)
+    output_file = "output.mp4"
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps = int(cap.get(cv2.CAP_PROP_FPS))
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter(output_file, fourcc, fps, (width, height), isColor=False)
     
-    # Save the uploaded video file
-    video_path = os.path.join("uploads", video.name)
-    video.save(video_path)
-
-    # Extract video details
-    video_clip = VideoFileClip(video_path)
-    video_duration = video_clip.duration
-    memory_usage = os.path.getsize(video_path)  # in bytes
-    process_time = time.time() - start_time
-    upload_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-
-    # Collect the log
-    log = {
-        "filename": video.name,
-        "collect_date_time": upload_time,
-        "video_duration": video_duration,
-        "process_time": process_time,
-        "memory_usage": memory_usage
-    }
-
-    # Save log in different formats
-    save_log(log)
-
-    return video_path, log
-
-def save_log(log):
-    # Save to CSV
-    csv_file = "logs.csv"
-    df = pd.DataFrame([log])
-    if os.path.exists(csv_file):
-        df.to_csv(csv_file, mode='a', header=False, index=False)
-    else:
-        df.to_csv(csv_file, index=False)
+    while(cap.isOpened()):
+        ret, frame = cap.read()
+        if not ret:
+            break
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        out.write(gray)
     
-    # Save to JSON
-    json_file = "logs.json"
-    if os.path.exists(json_file):
-        with open(json_file, 'r') as f:
-            logs = json.load(f)
-        logs.append(log)
-        with open(json_file, 'w') as f:
-            json.dump(logs, f, indent=4)
-    else:
-        with open(json_file, 'w') as f:
-            json.dump([log], f, indent=4)
+    cap.release()
+    out.release()
     
-    # Save to YAML
-    yaml_file = "logs.yaml"
-    if os.path.exists(yaml_file):
-        with open(yaml_file, 'r') as f:
-            logs = yaml.safe_load(f)
-        logs.append(log)
-        with open(yaml_file, 'w') as f:
-            yaml.dump(logs, f)
-    else:
-        with open(yaml_file, 'w') as f:
-            yaml.dump([log], f)
-
-def display_logs():
-    logs = []
-    if os.path.exists("logs.json"):
-        with open("logs.json", 'r') as f:
-            logs = json.load(f)
-    return logs
-
-# Create Gradio interface
-upload_video = gr.Interface(
-    fn=process_video,
-    inputs=gr.inputs.File(label="Upload Video"),
-    outputs=[gr.outputs.Video(label="Processed Video"), gr.outputs.JSON(label="Log Details")],
-    live=True
-)
-
-view_logs = gr.Interface(
-    fn=display_logs,
-    inputs=None,
-    outputs=gr.outputs.JSON(label="Logs History")
-)
+    return output_file
 
-app = gr.TabbedInterface(
-    [upload_video, view_logs],
-    ["Upload and Process Video", "View Logs"]
+demo = gr.Interface(
+    fn=convert_to_grayscale,
+    title="Video Upload and Display",
+    inputs=gr.Video(label="Upload Video", height=500, width=500),
+    outputs=gr.Video(label="Grayscale Video", height=500, width=500),
 )
 
-if __name__ == "__main__":
-    app.launch()
+demo.launch()