refactor: improve variable naming and streamline input processing in predict_formula.py

mineru/model/mfr/pp_formulanet_plus_m/predict_formula.py

@@ -68,13 +68,14 @@ class FormulaRecognizer(BaseOCRV20):
         batch_imgs = self.pre_tfs["UniMERNetImgDecode"](imgs=img_list)
         batch_imgs = self.pre_tfs["UniMERNetTestTransform"](imgs=batch_imgs)
         batch_imgs = self.pre_tfs["LatexImageFormat"](imgs=batch_imgs)
-        x = self.pre_tfs["ToBatch"](imgs=batch_imgs)
-        x = torch.from_numpy(x[0]).to(self.device)
+        inp = self.pre_tfs["ToBatch"](imgs=batch_imgs)
+        inp = torch.from_numpy(inp[0])
+        inp = inp.to(self.device)
         rec_formula = []
         with torch.no_grad():
-            with tqdm(total=len(x), desc="Formula Predict") as pbar:
-                for index in range(0, len(x), batch_size):
-                    batch_data = x[index: index + batch_size]
+            with tqdm(total=len(inp), desc="Formula Predict") as pbar:
+                for index in range(0, len(inp), batch_size):
+                    batch_data = inp[index: index + batch_size]
                     batch_preds = [self.net(batch_data)]
                     batch_preds = [p.reshape([-1]) for p in batch_preds[0]]
                     rec_formula += self.post_op(batch_preds)