Update app.py

app.py

@@ -1,47 +0,0 @@
-import json
-import gradio as gr
-import yolov5
-from PIL import Image
-from huggingface_hub import hf_hub_download
-
-app_title = "Object Detection"
-models_ids = ['StarAtNyte1/yolov7_custom']
-
-current_model_id = models_ids[-1]
-model = yolov5.load(current_model_id)
-
-
-
-def predict(image, threshold=0.25, model_id=None):
-    # update model if required
-    global current_model_id
-    global model
-    if model_id != current_model_id:
-        model = yolov5.load(model_id)
-        current_model_id = model_id
-
-    # get model input size
-    config_path = hf_hub_download(repo_id=model_id, filename="config.json")
-    with open(config_path, "r") as f:
-        config = json.load(f)
-    input_size = config["input_size"]
-
-    # perform inference
-    model.conf = threshold
-    results = model(image, size=input_size)
-    numpy_image = results.render()[0]
-    output_image = Image.fromarray(numpy_image)
-    return output_image
-
-
-gr.Interface(
-    title=app_title,
-    description="Created by ",
-    fn=predict,
-    inputs=[
-        gr.Image(type="pil"),
-        gr.Dropdown(models_ids, value=models_ids[-1]),
-    ],
-    outputs=gr.Image(type="pil"),
-    cache_examples=True if examples else False,
-).launch(enable_queue=True)