commit

app.py

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+import subprocess
+import tempfile
+import time
+from pathlib import Path
+
+import cv2
+import gradio as gr
+
+from inferer import Inferer
+
+pipeline = Inferer("human", device='cuda')
+print(f"GPU on? {'🟢' if pipeline.device.type != 'cpu' else '🔴'}")
+
+def fn_image(image, conf_thres, iou_thres):
+    return pipeline(image, conf_thres, iou_thres)
+
+
+def fn_video(video_file, conf_thres, iou_thres, start_sec, duration):
+    start_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec))
+    end_timestamp = time.strftime("%H:%M:%S", time.gmtime(start_sec + duration))
+
+    suffix = Path(video_file).suffix
+
+    clip_temp_file = tempfile.NamedTemporaryFile(suffix=suffix)
+    subprocess.call(
+        f"ffmpeg -y -ss {start_timestamp} -i {video_file} -to {end_timestamp} -c copy {clip_temp_file.name}".split()
+    )
+
+    # Reader of clip file
+    cap = cv2.VideoCapture(clip_temp_file.name)
+
+    # This is an intermediary temp file where we'll write the video to
+    # Unfortunately, gradio doesn't play too nice with videos rn so we have to do some hackiness
+    # with ffmpeg at the end of the function here.
+    with tempfile.NamedTemporaryFile(suffix=".mp4") as temp_file:
+        out = cv2.VideoWriter(temp_file.name, cv2.VideoWriter_fourcc(*"MP4V"), 100, (1280, 720))
+
+        num_frames = 0
+        max_frames = duration * 100
+        while cap.isOpened():
+            try:
+                ret, frame = cap.read()
+                if not ret:
+                    break
+            except Exception as e:
+                print(e)
+                continue
+
+            out.write(pipeline(frame, conf_thres, iou_thres))
+            num_frames += 1
+            print("Processed {} frames".format(num_frames))
+            if num_frames == max_frames:
+                break
+
+        out.release()
+
+        # Aforementioned hackiness
+        out_file = tempfile.NamedTemporaryFile(suffix="out.mp4", delete=False)
+        subprocess.run(f"ffmpeg -y -loglevel quiet -stats -i {temp_file.name} -c:v libx264 {out_file.name}".split())
+
+    return out_file.name
+
+
+image_interface = gr.Interface(
+    fn=fn_image,
+    inputs=[
+        "image",
+        gr.Slider(0, 1, value=0.5, label="Confidence Threshold"),
+        gr.Slider(0, 1, value=0.5, label="IOU Threshold"),
+    ],
+    outputs=gr.Image(type="file"),
+    examples=[["example_1.jpg", 0.5, 0.5], ["example_2.jpg", 0.25, 0.45], ["example_3.jpg", 0.25, 0.45]],
+    title="Human Detection",
+    description=(
+        "Gradio demo for Human detection on images. To use it, simply upload your image or click one of the"
+        " examples to load them. Read more at the links below."
+    ),
+    allow_flagging=False,
+    allow_screenshot=False,
+)
+
+video_interface = gr.Interface(
+    fn=fn_video,
+    inputs=[
+        gr.Video(type="file"),
+        gr.Slider(0, 1, value=0.25, label="Confidence Threshold"),
+        gr.Slider(0, 1, value=0.45, label="IOU Threshold"),
+        gr.Slider(0, 100, value=0, label="Start Second", step=1),
+        gr.Slider(0, 100 if pipeline.device.type != 'cpu' else 3, value=4, label="Duration", step=1),
+    ],
+    outputs=gr.Video(type="file", format="mp4"),
+    examples=[
+        ["example_1.mp4", 0.25, 0.45, 0, 2],
+        ["example_2.mp4", 0.25, 0.45, 5, 3],
+        ["example_3.mp4", 0.25, 0.45, 6, 3],
+    ],
+    title="Human Detection",
+    description=(
+        "Gradio demo for Human detection on videos. To use it, simply upload your video or click one of the"
+        " examples to load them. Read more at the links below."
+    ),
+    allow_flagging=False,
+    allow_screenshot=False,
+)
+
+webcam_interface = gr.Interface(
+    fn_image,
+    inputs=[
+        gr.Image(source='webcam', streaming=True),
+        gr.Slider(0, 1, value=0.5, label="Confidence Threshold"),
+        gr.Slider(0, 1, value=0.5, label="IOU Threshold"),
+    ],
+    outputs=gr.Image(type="file"),
+    live=True,
+    title="Human Detection",
+    description=(
+        "Gradio demo for Human detection on real time webcam. To use it, simply allow the browser to access"
+        " your webcam. Read more at the links below."
+    ),
+    allow_flagging=False,
+    allow_screenshot=False,
+)
+
+if __name__ == "__main__":
+    gr.TabbedInterface(
+        [video_interface, image_interface, webcam_interface],
+        ["Run on Videos!", "Run on Images!", "Run on Webcam!"],
+    ).launch()