Upload folder using huggingface_hub

README.md

@@ -1,12 +1,6 @@
 ---
-title: Video Maker
-emoji: 👀
-colorFrom: red
-colorTo: gray
-sdk: gradio
-sdk_version: 5.49.1
+title: Video-Maker
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 5.42.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,59 @@
+"""
+Gradio “still-image + audio → video” with API
+"""
+import gradio as gr, subprocess, uuid, math, pathlib, shutil, os, tempfile
+
+ALLOW_IMG = (".png",".jpg",".jpeg")
+ALLOW_AUD = (".wav",".mp3",".m4a",".flac",".aac")
+
+def make_video(image, audio):
+    """
+    Gradio wrapper: inputs are file-paths (str) supplied by the component
+    Returns: path to generated mp4
+    """
+    if not (image and audio):
+        raise ValueError("Need both image and audio")
+
+    uid   = uuid.uuid4().hex
+    tmpdir = pathlib.Path(tempfile.mkdtemp())
+    img_p  = tmpdir / f"{uid}_img{pathlib.Path(image).suffix}"
+    aud_p  = tmpdir / f"{uid}_aud{pathlib.Path(audio).suffix}"
+    out_p  = tmpdir / f"{uid}.mp4"
+
+    shutil.copy(image, img_p)
+    shutil.copy(audio, aud_p)
+
+    # audio duration
+    probe = subprocess.run(
+        ["ffprobe","-v","error","-show_entries","format=duration",
+         "-of","default=noprint_wrappers=1:nokey=1",str(aud_p)],
+        text=True, capture_output=True, check=True)
+    dur = math.ceil(float(probe.stdout.strip()))
+
+    # ffmpeg: still image looped + copy audio
+    subprocess.run([
+        "ffmpeg","-y","-loop","1","-i",str(img_p),"-i",str(aud_p),
+        "-c:v","libx264","-tune","stillimage","-pix_fmt","yuv420p",
+        "-c:a","copy","-shortest","-t",str(dur),str(out_p)
+    ], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+
+    return str(out_p)
+
+# ---------------- Gradio UI ----------------
+with gr.Blocks(title="Image + Audio → Video") as demo:
+    gr.Markdown("## Upload an image and an audio file to receive an MP4")
+    with gr.Row():
+        img_in = gr.Image(type="filepath", label="Image")
+        aud_in = gr.Audio(type="filepath", label="Audio")
+    btn = gr.Button("Generate video", variant="primary")
+    vid_out = gr.Video(label="Result")
+
+    btn.click(make_video, inputs=[img_in, aud_in], outputs=vid_out)
+
+# --------------- API exposure ---------------
+# gradio automatically creates /api/predict that mirrors btn.click
+# We also add an explicit named endpoint so users can discover it
+demo.queue()          # required for HF Spaces
+demo.launch(server_name="0.0.0.0",
+            server_port=int(os.getenv("PORT", 7860)),
+            share=False)

requirements.txt

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+gradio