Create app.py

app.py

@@ -0,0 +1,36 @@
+from model import SurfinBird
+from torchvision import transforms, io
+import csv
+import gradio as gr
+
+with open("birds.csv", "r") as r:
+  birds = list(csv.reader(r, delimiter=","))
+
+config = {"num_channels": 3, "hidden_units": 256, "num_classes": 525, "labels": birds}
+
+model = SurfinBird(config=config)
+model = SurfinBird.from_pretrained("ulichovick/birdnet")
+
+usr_img_transform = transforms.Compose([
+    transforms.Resize(size=(224, 224)),
+])
+
+target_image = io.read_image(str(image_path)).type(torch.float32)
+target_image = target_image / 255.
+target_image = usr_img_transform(target_image)
+
+model.eval()
+with torch.inference_mode():
+  target_image = target_image.unsqueeze(dim=0)
+  target_image_pred = model(target_image)
+target_image_pred_label = torch.argmax(target_image_pred, dim=1)
+
+#print(config["labels"][target_image_pred_label])
+
+gr.Interface(
+    transcribe,
+    inputs=gr.Image(label="gimme da bird"),
+    outputs=["textbox"],
+    title=titulo,
+    description=desc,
+).launch()