Upload app.py

app.py

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+import gradio as gr
+import torch
+import net
+import argparse
+from config import set_cfg, cfg
+from SpeakerNet import *
+import lossfunction
+from DatasetLoader import loadWAV
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--config_name", type=str, default="ECAPA_TDNN_data_cfg", help="the configs name that will as a base configs")
+parser.add_argument("--resume", default="train_models/epoch_37_ECAPA_TDNN2.48", type=str, help="resume path")
+args = parser.parse_args()
+global cfg
+assert args.config_name is not None
+if args.config_name:
+    set_cfg(args.config_name)
+cfg.replace(vars(args))
+del args
+
+device = torch.device("cpu")
+model = getattr(net, cfg.model)().to(device)
+loss = getattr(lossfunction, cfg.loss)(cfg.nOut, cfg.nClasses).to(device)
+model = SpeakerNet(model=model, trainfunc=loss, nPerSpeaker=cfg.nPerSpeaker)
+
+ckpt = torch.load("train_models/epoch_37_ECAPA_TDNN2.48", map_location="cpu")
+model.load_state_dict(ckpt['model_state_dict'], strict=False)
+print("checkpoint加载完毕!")
+
+model.eval()
+
+def SpeakerVerification(path1,path2):
+    inp1 = loadWAV(path1, max_frames=300, evalmode=True)
+    inp2 = loadWAV(path2, max_frames=300, evalmode=True)
+    # print(inp1.shape)
+    inp1 = torch.FloatTensor(inp1)
+    inp2 = torch.FloatTensor(inp2)
+    # print(inp1.shape)
+    with torch.no_grad():
+        emb1 = model(inp1).detach().cpu()
+        emb2 = model(inp2).detach().cpu()
+    emb1 = F.normalize(emb1, p=2, dim=1)
+    emb2 = F.normalize(emb2, p=2, dim=1)
+    dist = F.cosine_similarity(emb1.unsqueeze(-1),  emb2.unsqueeze(-1).transpose(0, 2)).numpy()
+    score = numpy.mean(dist)
+    print(score)
+    # threshold = 0.414
+    if score >= 0.414:
+        output = "同一个人"
+    else:
+        output = "不同的人"
+
+    return output
+
+inputs = [
+    gr.inputs.Audio(source="upload", type="filepath", label="Speaker #1", optional=False),
+    gr.inputs.Audio(source="upload", type="filepath", label="Speaker #2", optional=False)
+]
+
+
+examples = [["example/speaker1-1.wav", "example/speaker1-2.wav"],
+            ["example/speaker1-1.wav", "example/speaker2-1.wav"],
+            ["example/speaker2-1.wav", "example/speaker2-1.wav"],
+            ["example/speaker1-2.wav", "example/speaker2-2.wav"]
+            ]
+
+iface = gr.Interface(fn=SpeakerVerification, inputs=inputs, outputs="text", examples=examples)
+iface.launch(share=True)
+
+if __name__ == '__main__':
+    # print(SpeakerVerification("example/speaker1-1.wav", "example/speaker1-2.wav"))
+    pass