Create app.py

app.py

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+import torch
+import gradio as gr
+from huggingface_hub import hf_hub_download
+from PIL import Image
+
+REPO_ID = "owaiskha9654/Yolov7_Custom_Object_Detection" 
+FILENAME = "best.pt"
+
+yolov7_weights = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
+
+model = torch.hub.load('WongKinYiu/yolov7', 'custom', path=yolov7_weights, force_reload=True)  # local repo
+
+def object_detection(im, size=416):
+    results = model(im)  # inference
+    #results.print()  # print results to screen
+    #results.show()  # display results
+    #results.save()  # save as results1.jpg, results2.jpg... etc.
+    results.render()  # updates results.imgs with boxes and labels
+    return Image.fromarray(results.imgs[0])
+
+title = "Identificação de Defeitos em Banana"
+description = """Esse modelo é uma pequena demonstração baseada em uma análise de cerca de 60 imagens somente. Para resultados mais confiáveis e genéricos, são necessários mais exemplos (imagens).
+"""
+
+image = gr.inputs.Image(shape=(416, 416), image_mode="RGB", source="upload", label="Image", optional=False)
+outputs = gr.outputs.Image(type="pil", label="Output Image")
+
+gr.Interface(
+    fn=object_detection,
+    inputs=image,
+    outputs=outputs,
+    title=title,
+    description=description,
+    examples=[["sample_images/IMG_0125.JPG"], ["sample_images/IMG_0129.JPG"], 
+              ["sample_images/IMG_0157.JPG"], ["sample_images/IMG_0158.JPG"]],
+).launch()