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README.md

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 ---
 title: Forklift Object Detection
-emoji: ⚡
-colorFrom: purple
+emoji: 🎮
+colorFrom: red
 colorTo: gray
 sdk: gradio
 sdk_version: 3.15.0

app.py

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+
+import json
+import gradio as gr
+import yolov5
+from PIL import Image
+from huggingface_hub import hf_hub_download
+
+app_title = "Forklift Object Detection"
+models_ids = ['keremberke/yolov5n-forklift', 'keremberke/yolov5s-forklift', 'keremberke/yolov5m-forklift']
+article = f"<p style='text-align: center'> <a href='https://huggingface.co/{models_ids[-1]}'>model</a> | <a href='https://huggingface.co/keremberke/forklift-object-detection'>dataset</a> | <a href='https://github.com/keremberke/awesome-yolov5-models'>awesome-yolov5-models</a> </p>"
+
+current_model_id = models_ids[-1]
+model = yolov5.load(current_model_id)
+
+examples = [['test_images/32LSCZQDHZO7_jpg.rf.8fddaa4b5ed4db87d19a32d4554b9c23.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/6URLZIZIQ6S0_jpg.rf.4661cb4082077e616ec94250eea6328f.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/I91P1I5WNUZT_jpg.rf.c5c49a5f421751c30008a35e7b52087e.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/JWF31R9STW0L_jpg.rf.a785b0107b333fe746fe1c4c8d2f744f.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/LTDX8N8ZKBT2_jpg.rf.6e09889a432d15c19fa0fbdbb62d347f.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/M_01685_png.rf.57a2823eabfa135c0a508d18faa70ce3.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/M_03339_png.rf.f755ccc7bdf2a0ebc7e4553a0576ed50.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/M_04045_png.rf.31bd5eed4b55dbcafe568210774cb5dc.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/M_04302_png.rf.62eabd3a1cc0dbfcdffa9c5a9582f77c.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/M_07555_png.rf.9c2d725a383658227bc87891f68fe975.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/M_08430_png.rf.64508c4e583f64ac2cd431c99dc79834.jpg', 0.25, 'keremberke/yolov5m-forklift'], ['test_images/V75EBJ0AG2HV_jpg.rf.88822c95c57d6bfb33092eb5ec0a020c.jpg', 0.25, 'keremberke/yolov5m-forklift']]
+
+
+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 'keremberke'",
+    article=article,
+    fn=predict,
+    inputs=[
+        gr.Image(type="pil"),
+        gr.Slider(maximum=1, step=0.01, value=0.25),
+        gr.Dropdown(models_ids, value=models_ids[-1]),
+    ],
+    outputs=gr.Image(type="pil"),
+    examples=examples,
+    cache_examples=True if examples else False,
+).launch(enable_queue=True)

requirements.txt

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+
+yolov5==7.0.5
+gradio==3.15.0
+torch
+huggingface-hub