Duplicate from Future-Tense/Slo-Mo-YOLO-Video

Co-authored-by: Future-tense <[email protected]>

.gitattributes

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README.md

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+---
+title: Slo-Mo YOLO8s Video
+emoji: 🥴
+colorFrom: blue
+colorTo: gray
+sdk: gradio
+sdk_version: 3.18.0
+app_file: app.py
+pinned: true
+duplicated_from: Future-Tense/Slo-Mo-YOLO-Video
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import time
+import cv2 # opencv2 package for python.
+import torch
+from pytube import YouTube
+from ultralyticsplus import YOLO, render_result
+
+
+model = YOLO('ultralyticsplus/yolov8s')
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+URL = "https://www.youtube.com/watch?v=6NBwbKMyzEE" #URL to parse
+
+# set model parameters
+model.overrides['conf'] = 0.50 # NMS confidence threshold
+model.overrides['iou'] = 0.45 # NMS IoU threshold
+model.overrides['agnostic_nms'] = False # NMS class-agnostic
+model.overrides['max_det'] = 1000 # maximum number of detections per image
+model.to(device)
+
+
+def load(URL):
+ 
+ yt = YouTube(URL)
+ vid_cap = yt.streams.filter(progressive=True, file_extension='mp4').order_by('resolution').desc().last().download(filename="tmp.mp4")
+ global player
+ player = cv2.VideoCapture(vid_cap)
+ frame_num = int(player.get(cv2.CAP_PROP_POS_FRAMES))
+ frame_count = int(player.get(cv2.CAP_PROP_FRAME_COUNT))
+ frame_fps = (player.get(cv2.CAP_PROP_FPS))
+ tog = 0
+ return vid_cap,frame_num,frame_count,frame_fps,tog
+ 
+def vid_play(cap,frame_num):
+ assert player.isOpened() # Make sure that their is a stream. 
+ player.set(cv2.CAP_PROP_POS_FRAMES, int(frame_num))
+ ret, frame_bgr = player.read(int(frame_num))
+ frame = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB) 
+ results = model.predict(frame)
+ render = render_result(model=model, image=frame, result=results[0])
+ return render
+
+def fw_fn(cur,last):
+ next = cur+1
+ if next > last:
+ next = last
+ return next
+def bk_fn(cur):
+ next = cur-1
+ if next < 0:
+ next = 0
+ return next
+def tog_on():
+ return 1,gr.Markdown.update("""<center><h7>Status: Playing 😁</h7></center>""")
+def tog_off():
+ return 0,gr.Markdown.update("""<center><h7>Status: Stopped 💀</h7></center>""")
+ 
+def pl_fn(cap,cur,last,fps,pl_tog):
+ player.set(cv2.CAP_PROP_POS_FRAMES, cur)
+ ret, frame_bgr = player.read(cur)
+ frame = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB)
+ results = model.predict(frame)
+ render = render_result(model=model, image=frame, result=results[0])
+ if pl_tog ==1:
+ cur+=1
+ else:
+ cur = cur 
+ return render,cur
+
+with gr.Blocks() as app:
+ gr.Markdown("""<center><h1>Slow Video Object Detection</h1><h4>Gradio and ultralyticsplus/yolov8s</h4><h4>Probably faster on GPU 🤷‍♂️</h4></center>""")
+ play_state = gr.Markdown("""<right><h7></h7></right>""")
+
+ with gr.Row():
+ with gr.Column():
+ youtube_url = gr.Textbox(label="YouTube URL",value=f"{URL}")
+ load_button = gr.Button("Load Video")
+ output_win = gr.Video()
+ with gr.Column():
+ with gr.Row():
+ cur_frame = gr.Number(label="Current Frame")
+ fps_frames = gr.Number(label="Video FPS",interactive=False)
+ total_frames = gr.Number(label="Total Frames",interactive=False)
+ #run_button = gr.Button()
+ with gr.Row():
+ bk = gr.Button("<")
+ pl = gr.Button("Play")
+ st = gr.Button("Stop")
+ fw = gr.Button(">")
+ det_win = gr.Image(source="webcam", streaming=True)
+ with gr.Row():
+ pl_tog=gr.Number(visible=False)
+ ins_cnt=gr.Number(visible=False) 
+ pl.click(tog_on,None,[pl_tog,play_state],show_progress=False)
+ st.click(tog_off,None,[pl_tog,play_state],show_progress=False)
+ pl_tog.change(pl_fn,[output_win,cur_frame,total_frames,fps_frames,pl_tog],[det_win,cur_frame],show_progress=False)
+ cur_frame.change(pl_fn,[output_win,cur_frame,total_frames,fps_frames,pl_tog],[det_win,cur_frame],show_progress=False)
+ bk.click(bk_fn,[cur_frame],cur_frame,show_progress=False)
+ fw.click(fw_fn,[cur_frame,total_frames],cur_frame,show_progress=False)
+ load_button.click(load,youtube_url,[output_win,cur_frame,total_frames,fps_frames,pl_tog])
+ #run_button.click(vid_play, [output_win,cur_frame], det_win) 
+
+app.queue(concurrency_count=10).launch()

requirements.txt

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+torch
+opencv-python
+pytube
+ultralyticsplus==0.0.14