Create app.py

app.py

@@ -0,0 +1,41 @@
+import os
+os.system('wget https://huggingface.co/spaces/An-619/FastSAM/resolve/main/weights/FastSAM.pt')
+
+import yolov5
+
+# load model
+model = yolov5.load('keremberke/yolov5m-license-plate')
+
+# set model parameters
+model.conf = 0.5  # NMS confidence threshold
+model.iou = 0.25  # NMS IoU threshold
+model.agnostic = False  # NMS class-agnostic
+model.multi_label = False  # NMS multiple labels per box
+model.max_det = 1000  # maximum number of detections per image
+
+# set image
+def license_plate_detect(img):
+    # perform inference
+    results = model(img, size=640)
+    
+    # inference with test time augmentation
+    results = model(img, augment=True)
+    
+    # parse results
+    if len(results.pred):
+        predictions = results.pred[0]
+        boxes = predictions[:, :4] # x1, y1, x2, y2
+        scores = predictions[:, 4]
+        categories = predictions[:, 5]
+        return boxes
+
+from PIL import Image
+# image = Image.open(img)
+import pytesseract
+
+def read_license_number(img):
+    boxes = license_plate_detect(img)
+    if boxes:
+        return [pytesseract.image_to_string(
+                    image.crop(bbox.tolist()))
+               for bbox in boxes]